Cole Hons: Greetings, Fellow Homo sapiens, and welcome to The Symbiotic Podcast. For this episode, we dive into the greatest unsolved mystery of 2020: “Where did SARS-CoV-2 — the virus that causes COVID-19 — come from?” From the earliest days of the outbreak, the international community has wanted to know the details of precisely where, when and how this virus emerged.

The official story put forth by the Chinese government, that the virus originated in a Wuhan wet market, fails to give us a definitive picture and leaves many questions unanswered. The proximity of that particular wet market to the Wuhan Institute of Virology — China’s highest-security facility for studying viruses — has fueled speculation that the virus may have escaped from, or even been created in, a Chinese lab. As a result of all this, we have seen multiple theories and politically motivated accusations fly in 2020. US government officials blaming China. Chinese officials blaming the US Army. All the while, the global scientific community has been struggling to do the hard work of science, trying to understand where this virus came from, and how we might halt its terrifying toll on the world’s population.

Today’s guests are part of that global community of scientists. All of them are members of Penn State’s Center for Infectious Disease Dynamics, and all of them are deeply involved in ongoing international efforts to piece together a bigger picture of how and why new viruses emerge and spillover from other species to our own.

Maciej Boni is an Associate Professor of Biology at Penn State. He analyzes the epidemiology and evolution of both human and avian influenza, and evaluates strategies to treat and prevent diseases, particularly in southern Vietnam. Sagan Friant is an Assistant Professor of Anthropology at Penn State. Her works focuses on the evolutionary anthropology of human health, disease ecology, nutrition, socio-ecological systems, and bushmeat hunting, through field research in Nigeria. And Peter Hudson is Willaman Professor of Biology at Penn State, and former director of the Huck Institutes of the Life Sciences. Much of Hudson’s work has implications for the control of wildlife diseases and emerging zoonotic disease across the globe.

I hope you’ll enjoy this lively conversation about the possible origins of SARS-CoV-2, wildlife spillover, and the factors that drive the emergence of new diseases – some of which have nothing to do with laboratory science at all.

---

Intro (Nina Jablonski): Evolution involves more than the survival of the fittest. It's also about the survival of the most cooperative, and mutually beneficial relationships are critical to the survival of every species. Welcome to The Symbiotic Podcast, where we will explore the collaborative side of life and work to consciously evolve science itself.

Cole: Hello folks. Thanks so much for being on The Symbiotic Podcast today. It's a real honor to have you all on the show with us. Thank you so much for your time. All of you are from Penn State. All of you are members of Penn State's Center for Infectious Disease Dynamics, and that's a very collaborative interdisciplinary space. Though we're not going to talk today about a specific project that you all worked on together, we are going to benefit from your collective knowledge around this whole topic of where do viruses come from, specifically, where did SARS-CoV-2 come from and other similar viruses? How does spillover occur? It's such an important topic globally right now.

Just this month, on November 3rd, to be exact, David Relman from the Department of Medicine at Stanford published an opinion piece in the Proceedings of the National Academy of Sciences titled To Stop the Next Pandemic, We Need to Unravel the Origins of COVID-19. That's a huge important thing that people are working on internationally. In his piece, he puts forth the fact that we need to put politics aside and we need to be transparent and we need to work as an international scientific community to get down to the origins of this virus. One of our guests today, Maciej Boni, recently published a paper just at the end of July of this year in collaboration with an international team of scientists in the journal Nature Microbiology. This paper is on the evolutionary origins of the virus, so Maciej's going to be leading off our conversation today to get us into that topic.

Also, I'll mention that Maciej was featured in a video produced by Business Insider called How We Know the Coronavirus Wasn't Made in the Lab. We're going to share the link to both that paper and the video in the notes to this podcast. So Maciej, a question for you. In spite of all the various theories floating around out there alleging that SARS-CoV-2 escaped from a Chinese lab either accidentally or on purpose, there seems to be a general scientific consensus that this is not the case. Can you please tell us why?

Maciej Boni: Sure. Yes, what you said is accurate. The general scientific consensus is that the virus crossed over from animal populations, specifically bat populations, into humans in some part of China, and we're just not sure where. The genetic link exists showing us which bat populations and which bat lineages it would have crossed over from. The reason that this is a consensus among scientists is that these types of crossing over, or these types of emergence events, have happened a lot in the past. We've seen avian influenza viruses jump from geese to humans, Ebola viruses jump from bats to people, we've seen MERS jump from camels to people. So these are pretty common occurrences, and once you've got the genetic links, it's a perfectly normal conclusion to come to.

So to address some of these other possibilities. Could it have come from a lab, and if it did, was it intentional or was it an accident? These are worth discussing. Laboratory accidents do happen. The 1977 Russian flu that caused an influenza pandemic, that was either a laboratory accident or an accidental release from a clinical trial. There was a 1978 smallpox accident where, in the UK, a smallpox virus escaped from a lab and infected a few people. Very small number of people, but still potentially very dangerous. So these things happen. It's necessary to investigate them. We won't have access to records, of course, at the Wuhan Institute of Virology, which is where the purported escape would have occurred. But we also don't see any signals that are common with a lab escape.

For example, there's no cases among the staff at the Wuhan Institute of Virology. There were no cases of respiratory disease or pneumonia, or certainly any confirmed viral infections, and everybody tested antibody negative, indicating that the virus didn't infect any individuals that worked there. So then when you read the news, people will reply and they'll say, "Well, it was all covered up." When you start having this discussion, you quickly see that it's a little difficult to convince people because there's always this answer that it could have been a coverup.

The problem is that this is a pretty challenging coverup to put together. Imagine that the virus accidentally escaped from a lab and it began infecting a few employees and a few scientists that worked there, and then maybe their family or their contacts. You wouldn't really know that any of this happened until three, four, five weeks later, people started showing up in hospitals with some unidentifiable pneumonia. And then after this unidentifiable pneumonia was flagged as important, it would take another few weeks to sequence the virus and develop a diagnostic. So now you're already six or seven weeks into this epidemic and you're now going to have to do a coverup that goes back in time and covers up all these cases that have already been reported to health systems and possibly reported internationally. So I don't really see how someone could have pulled off this type of coverup.

I think the final hypothesis that is talked about is that this was intentionally released. I don't really understand why someone thinks it would have benefited China to release a virus accidentally in its own population and out to the world. And how would they know that the virus was deadly? How would they know that the virus could transmit from person to person? So unless they were doing experiments on people ... and to suggest something like this, you'd need some body of evidence to suggest that something extraordinarily unethical and horrific was being done ... they wouldn't know that this was a virus that had the possibility to spread this way. So it's talked about a lot, but until somebody produces some evidence on the laboratory origin hypothesis, the best evidence points to this being a natural occurrence from animal populations to human populations.

Cole: Thank you. Appreciate you digging deeper to break that out for us.

Maciej: Sure thing, Cole.

Cole: How do you even determine the origin of a virus? Let's dig in here.

Maciej: Sure. To determine the origin of anything, you've got two tools to start with. You start with the genetics and fossils. With viruses, obviously, you don't have a huge opportunity to look at fossil evidence, but it's not zero. You can sometimes find viruses in frozen corpses that you can look at from 100 years ago. But the majority tool you have for viruses is genetics. So you have to be able to know how quickly the virus is evolving and then you have to use that speed of evolution to be able to look back in time to see at what point in time that it crossed some boundary, it changed from one form to another or maybe moved from one population to another population.

So if a virus has been circulating only in humans, this is really difficult because there's no origin that you can look for if you only have human evidence of transmission. You can just kind of point to viral circulation and say it's always been in humans. The methods that allow you to look backwards, they don't really allow you to look back more than about 100 years. Viruses evolve very quickly, so 100 years of viral evolution is a lot of evolution. So the situation where you can actually determine origins for human viruses is where you have a virus that's been circulating in humans and in animal populations. The game or the trick here is to find a virus in animal populations that's similar to viruses that are already in human populations, and then you use genetics and the rate of evolution to start decoding how quickly or how recently and also maybe how often it's been jumping from animal populations into human populations.

Cole: Got it. Thank you.

Peter Hudson: There is another approach there, isn't there Maciej? I totally accept what you say, but in some instances, we can actually use epidemiology and tracing to find out who patient zero has been. In infections ... and I work on the Hendra virus infection ... we know, for example, the horse that got infected and then the first person who got infected with the virus, or that we believe, so we can actually see the virus in both the horse and the person and then we have to find the wildlife. So epidemiological tracing can help you in certain circumstances, and that's the real issue here with COVID-19, with SARS-CoV-2. We don't know the individual that first got infected, and I suspect but I don't know that there are political issues, or there are huge political issues around that. But it would be very nice to do the tracing, and I wonder if the Chinese have done this in Wuhan to identify the early people in this pandemic.

Maciej: Yeah, Pete's right about that. If you have everything in front of you, if you have a surveillance system that in real time is looking at the human infections and the animal infections and you're logging movements of animals, say, from some farm to another where you know there were or weren't infections, then you can just use all this epidemiological data to see in this matter of weeks, probably, how the infection jumped from one population to another.

Sagan Friant: I'd also say that the standard epidemiological approaches in using a certain number of questions and surveillance can be a little bit limiting. In a lot of viruses ... I work on a virus called monkeypox that we know is transmitted from, actually, rodents most likely, but we don't really know the host range. So similar to coronavirus, there's a limit to our knowledge, and so trying to find those initial pieces where the virus has spilled over into people and then doing really in-depth analysis, not just contact tracing but ethnographic work that looks at how humans in environments where viruses are spilling over, the diverse ways that they interact with wildlife kind of as a starting point to even inform more quantitative epidemiological approaches and form those questions that we can ask at a broader scale.

Peter: Sagan's point brings us forward and says, "What are the surveillance mechanisms that we actually need in place?" And it seems to me so blatantly obvious that we need to be doing surveillance of people at the human wildlife intersection. Sagan was referring to some types of people who may have contact with dead animals and things like this. Obviously, those people in wet markets in places like Wuhan should have surveillance taking place.

Doing surveillance for the virus itself is not always a sensible thing, because an infection can last just a few days and unless you miss that infection ... as we know for COVID-19 ... then you're not going to get ... that isn't the right response variable you should get. But now it's developments in looking at serology and antibodies ... and I'm thinking, of course, here Maciej, Sagan, about VirScan. We should be using the VirScan-type approach to see what people have been exposed to. So we should be banking [inaudible 00:07:16], I think, in the surveillance systems for the future.

Sagan: Yeah. I agree completely. So much of the surveillance in the settings that I work are conducted in hospital settings, so your knowledge on what is emerging in these settings is limited to people who can physically report to hospitals. There's so many social and environmental variables, especially in rural areas where a lot of viruses are emerging that mean that people aren't reporting to hospitals. So you're missing so much information and only getting those that are able to seek healthcare in establishments that are able to detect novel infections, so there's a lot of barriers there.

Cole: And are these barriers common to all coronaviruses? I know, Maciej, you and I had an exchange about the origin of viruses is tough to begin with, but for coronaviruses, it's particularly tough. Is it because of the things that you all have been breaking out just now? Or are there other-

Maciej: Yeah, that's right. There have been three coronaviruses that have emerged into human populations in the last 20 years and two of them had low transmission and a trickle of cases. Because that transmission was low, we were able to take an epidemiological approach to start looking at animal markets and camel farms to see where these spillover events were happening. If you have a dozen cases, you can begin an epidemiological investigation like that, but if you have 5,000, you can't, not only because of the number, but if you have 5,000 cases, the origin was six weeks ago. You've missed everything.

For SARS-CoV-2, that's what happened. We missed everything. Transmission was too high. We did not detect it at the first seven cases. We detected it at the first 40 cases, but those 40 were probably from a group of several thousand that had developed pneumonia and were at a hospital. So on December 30th last year when the first report came out, it was already six weeks too late.

Peter: This is partly why I think David Relman's paper in PNAS is actually wrong. We do not actually need to know the origin of this virus to prevent the next outbreak, because the next outbreak could maybe be a coronavirus, or it could be some other type of virus taking place. So we don't actually need to know the origin of this to prevent the next one, but what we need to do is we need to understand the drivers, why these diseases are emerging, and we also need to understand when and how they're spilling over. Wet markets is an obvious place where they spill over because people are coming into close contact with wild animal species, and that is not a sensible thing to do. It's very easy to say ... and we said this back in 2003 ... "Don't eat bats or civet cats." The Chinese were meant to stop doing that, but they turned a blind eye to what was happening.

Cole: I see. Well, let's get into the mechanics of spillover a little bit for people who don't ... I mean, I think in the popular consciousness, you just go, "Okay, you eat a bat, the bat gets you sick." Is it really that simple? Or what are some of the other mechanics of the ways that zoonotic spillover happens, where these viruses move from animals to people? Are there many, many different routes? Because I've heard it's, what, 60, 70% of viruses we deal with have some sort of spillover element from animals to people. Is that correct?

Peter: Yes, and I suspect that most of our infections ... So you look at things which are considered human specialist infections, like measles. If you use this sort of magic approach, you would say, "Well, this spilled over from rinderpest," because we can follow it back as it were by using genomics. And similarly, we know HIV came from chimpanzees. In my study, which is on Hendra viruses that come from bats into humans, they use horses as a bridging host. So the bats infect the horses and then the horses infect the humans. And similarly in Nipah virus we work on, the bats infect palm sap that people then drink. So there's always an intermediate in each of these cases.

I think a very important question is, why is this taking place now? The research that I'm doing with my colleague, Raina Plowright, is showing that what is really taking place is that we're losing habitat, we're losing resources for the bats to feed on, and as a consequence of this, they're starving, and when they're short of resources, that's when they start shedding virus. They move into these poor habitats, they change their behavior. They often move into urban areas, increasing their contact with humans, increasing their contact with peridomestic hosts such as the horse or your dog or your rat or the rats and mice that live in your house, and that spillover then results in the virus actually reaching through to you.

So going back to the Relman paper, he suggests there's two routes that COVID came in. He says one of those is through a bridging host, an intermediate host, or it was a direct infection of a human that got into a lab. Well, I can think of multiple other routes of infection that took place, and we know that with ... Well, we know with betacoronaviruses, that in Wuhan, where we think the bats would have come from, that there have been previous spillover cases taking place. Now, I'm not saying that was SARS-CoV-2, but probably a betacoronavirus from the serology data that was published from there.

Cole: I see. And Maciej, with that paper we just talked about a minute ago, what were your core findings that we can share with our audience? And we'll do a link to that paper as well in our notes.

Maciej: Well, I didn't think there was very much new in that paper. I mean, Pete, if there's something I'm missing, and Sagan as well, please just let me know. But, I mean, since 1997, the emerging infectious disease community has been on alert for emerging viruses and there have been dozens, probably scores, of examples where there have been spillovers that have been addressed with epidemiological means because they happen in front of you and you can trace them. There have been dozens of cases where you don't get to see the immediate spillover, but you see it a few weeks later and you begin tracing it with genetics. Some of these have turned into pandemics. Some turned into large regional epidemics. And all of them, the epidemic and the postmortem, have turned back into that initial moment when things were ignored when they shouldn't have been when there was spillover occurring from animal into human populations.

They do invariably get back to the human and animal contacts, into market situations. But it's also true that every single spillover is different. The social and biological factors around an avian influenza spillover are different than for Ebola virus or Lassa virus. So, I mean, each one does need its own sort of program around it to see which parts are capable of being surveilled and on which side of the animal-human boundary we get the biggest benefit of paying attention right there. Sagan, you're doing this work. What's the type of work you can do around Lassa surveillance that allows you to detect the first signals of a spillover?

Sagan: Lassa virus is a rodent-borne hemorrhagic fever virus and luckily, as far as we can tell, it's primarily a single host system, which makes it a lot easier to understand because you're just looking at human interactions with a single animal, not a whole ecological community or unknown group of animals. And so surveillance, similar to what Pete was saying before, is looking at antibody responses, so you have a large number of infections that don't actually result in any clinical symptoms. So you have people getting infected with Lassa virus and at that point of spillover with limited human-to-human transmission. So it means that it's actually a pretty tangible system in which we can understand the spillover process because a majority of the infections are coming from reservoir hosts.

Now, this is different from coronavirus, which may be a single spillover event, then a transmission train that leads to a global pandemic, or same with HIV/AIDS or Ebola. So looking at systems like this in which you can actually study human-rodent contact and look for risk factors for transmission are pretty unique when studying spillover and really helpful to understand. And then one thing ... I'm in the Anthropology Department, so I'm interested in more of the nuances of human behavior, so looking beyond kind of these simple tallies of human-wildlife contact and epidemiological risk factors to the ways that humans construct and modify their environments. Similar to what Peter was saying with Hendra virus, that it's human modifications on the environment that can have downstream effects on shedding of the virus.

Well, in the Lassa system, you see humans almost constructing the ecological niche for the reservoir host through agricultural practices. So a lot of the reservoir biology is tied to human behaviors that plant all the food for the rodent and then all the sudden harvest all the food for the rodent and store it in the house, and then all the rodents can come into the house where all the food has gone. So the population dynamics and the movement and the contact in the household setting is influenced by a wider variety of human-environment interactions. This is true of a lot of spillover processes, and so agreeing with that was said before is I don't think that we need to know the origins of SARS ... I mean, we all want to know the origins of SARS-CoV-2, but this is part of a much broader pattern that people are studying in systems globally, including here in the US with Lyme disease, so this is something that we're starting to get a handle on and something that we know is happening and we know is happening at an increasing frequency.

So we have the knowledge. We're still missing a lot of knowledge and that leaves a lot of productive room for research, but it's part of a larger problem and elucidating the origins of SARS-CoV-2 will help contribute to our understanding, but it's not going to have a fundamental shift in our understanding of spillover because we know that these wildlife markets are really important areas for mixing viruses between animal hosts and between animal hosts and human hosts.

Peter: Sagan's work here is really important because it's bringing human behavior and an understanding of the biology, virology, and dynamics in these emerging diseases together. There's been a real block between those, and this is something that's ... Bringing the social and life sciences together even in the bigger context is extremely important. This is the way we're going to have a better insight into it. Very important.

Cole: Absolutely. I hear you both echoing some comments that were made back in February at the very ... It wasn't even called a pandemic yet. When this thing first hit, we had several of your colleagues from CID on. We had Matt Ferrari and Beth McGraw and Nita Bharti, and we talked about encroachment into wild spaces, we talked about this more anthropological, ecological view, the social piece of it, whether or not you're eating bats in a wet market, where you're building your houses, where you're disrupting ecosystems. It seems like that's where we have to get to with this. There's a lot of noise out there on the internet and all over the place in terms of where did this thing come from, and it does get politicized and people can go down all sorts of rabbit holes with that, but I agree with you that to step back and have this broader context of all the different forces at play is ultimately going to take us to a better place where we can do better as a society ... as an emerging global society, particularly ... to help prevent more of these things from happening.

With that in mind, do we even have enough understanding of spillover at this point to be able to start predicting it or preventing it? Where are we with that, in your opinion?

Peter: I do think actually making predictions about things you have no data on is almost impossible. So to actually make predictions about SARS-CoV-2 would have been totally and utterly impossible, to my mind. Mind you, we can come up with the bigger things and say if you're going to get infected ... you're going to get infected if you start eating bats, you're going to get infected if you start removing your forests and these animals are going to be dying, et cetera.

With the Hendra virus system, we have been able to pick up a couple of signals that take place, which have allowed us to predict future outbreaks of the disease. We've done this a priori for the last two outbreaks. We predicted where and when the outbreaks are going to occur because we see changes in the climatic conditions that drive what the bats actually do, and we also start to see signals in the reproduction of the bats, and we start to see signals where people who are bat carers in Australia have an increase in the number of babies they're taking in. So when we look at those signals, we can say, "We believe there's going to be an outbreak."

That's worked really well for the past two outbreaks. Then we had an outbreak this year which we predicted was going to take place and it didn't take place. The really nice thing was that there was an unexpected flowering of a tree that we didn't expect to be flowering this year, but it flowered at just the right time and saved the bats' resources, so they didn't starve. So it was like we made the prediction, but, of course, we assume, "This isn't going to happen," and then it did happen. So that was quite nice.

But that doesn't get us to the real mechanisms. Those are looking at signals of things that are going on that lead up to it. Those aren't saying, "Okay, the bats are like this and the virus is like this and the landscape is like this and the horses are hungry, so everything lines up." It's just taking signals out of that and saying that we can make predictions. But as I said, they're not really mechanisms.

Cole: Again, to hear you say that, it's fascinating to think that a tree could come into the system and change everything. All those different factors at play, so we have to have a better map, we have to have a more nuanced map, we have to be able to map all these different factors. And then just to be able to see the patters and read the signals, as you say, to be able to at least have a warning system, perhaps? Like an early warning system rather than a predictive system? Is that how you'd characterize that?

Peter: Yeah.

Sagan: Yeah.

Peter: Yes, I think that's pretty nicely put, yeah. Were you going to say something?

Sagan: One of the challenges is this disconnect between ... You have these broad forecasting models that are looking at maybe these really broad scale markers of spillover, so land use change, poverty, population change. Then you have people like me doing these really small-scale studies that often take place in a single village or a handful of villages that can really tease apart what's happening in this one spot, but maybe it's really different over there in another state or another part of the world. And so what we've been trying to do with Lassa virus is work together with these broad scale modelers who have targeted these key axes of risk that look at Lassa fever virus across Nigeria and trying to design local scale studies that help us understand how these broad scale risk factors actually translate into local scale processes.

So what does it mean that Lassa virus is associated with poverty? Is it in rural areas, or is it because poverty is associated with food insecurity and those are the people who eat rats? Or is it that poverty is associated with the way you construct your house, and that allows rodents to come in and infest your house? Or maybe the environment that you build your house, it's on the outskirts of the community. There's all ways that these kind of predictive factors can translate to actual human-wildlife interactions on the ground, and trying to tease those apart in a way that helps these two scales work together and across levels and can feed into these broad scale models, and then you can actually improve your forecasting measures, whether it's a single disease system or some of these much broader efforts that are just trying to predict spillover in general at a global scale, which is very challenging.

Cole: It sounds like it's a hyperlocalized thing that you're doing, but if the hyperlocalized approach could then be distributed globally to the different environments, maybe the principles could be applied to those specific places and ecosystems. Can you break out for our viewers and listeners to this a little bit, Sagan. It sounds fascinating as you're talking about a specific village and poverty, which again echoes what I heard from your CID colleagues back in February that poverty is a huge factor that's left out of the equation and the conversation. We're all talking about vaccines and we're all talking about medication, et cetera, but nobody's really looking at the underpinnings broadly of disease coming forward where we have to talk about things like poverty. But could you just tell us a little bit more about your specific research in that village? What does that actually look like to people participating?

Sagan: Sure. There's a concept in anthropology that I think is really helpful for just thinking about this in a more holistic manner, and it's called syndemics, so synergistic epidemics. It kind of extends the concept of comorbidities ... so two diseases interacting to worsen each other ... to social issues like poverty, and you could theoretically even extend it to ecological issues. So you have these different epidemics ... maybe of food security ... that are also working together with emerging infectious diseases and they're both exacerbated by it.

And so in the example of poverty and lack of access to resources and globalization are all feeding into a lot of these human-wildlife interactions. So one of my study projects focuses not on ... It's kind of pathogen diagnostics, so it doesn't focus on a specific pathogen, but it focuses on hunting of wildlife in West Africa, which is known there as bushmeat, and really focuses on understanding the larger social drivers of interaction between humans and wildlife through hunting, but also not through hunting. All the diverse ways that people interact with wildlife in these settings, some of which is driven largely by poverty. I think a lot of times, people think about this as people are hungry, so yeah, you can't take their food away from them.

But a lot of times, these populations aren't even subsisting off of wildlife. They're selling it for money to send their children to school or to build a better house or to fix the roof, and so there's a large dimension of this wildlife trade that really extends human-wildlife interfaces and the levels of contact beyond what you would normally see in a rural hunting community that is subsistence based. Because now you have these levels of extraction that are not only feeding this one little village, but they're feeding Calabar, the nearest city, they're feeding Lagos, the most populated city in all of Africa, and they're being flown to the US and Europe and that's creating a really large amount of human-wildlife contact. In addition to that, people don't have access to healthcare, so they're looking to [crosstalk 00:28:39] to treat their diseases.

So there's all these different forms of contact with wildlife through hundreds of different types of medicinal uses that people in one community are looking to wildlife to treat various illnesses that are also constructing different pathways of possible transmission, some of which may be riskier than just consuming ... The consumption of a cooked animal may be not that risky, but dealing with animal parts as rubs and applying them to different parts of the body, especially when they're in a raw condition, can really facilitate potential transmission. So we're just trying to get a better idea of how that is influenced by where of villages and who a person is. So kind of looking within a single village, who hunts and who doesn't? There's a huge range of people, and what makes one person decide to hunt and another person not to hunt?

I really came across this question ... Before I was doing research, I was helping with a conservation NGO in controlling poachers and the first hunter that I came across was a 15-year-old boy who was almost at tears when he saw us walk up into the hunting shed. He had a dead monkey. This just blew away all of my preconceptions on what a poacher or bushmeat hunter looked like, and so these are often children. We found that large family sizes and low income and a certain age range all influenced whether people hunt as part of their livelihoods, as well as family tradition in these areas, and that maybe it's a lack of access to educational resources and livelihood opportunities that drive just a certain subsection of the population into hunting, which is not a desirable livelihood. While as others who maybe have more capital are able to leave the community, engage in trade and other aspects that can help improve their livelihoods.

And often ... I'll just add finally that hunting can be a fallback livelihood. So having a hunter and a non-hunter is a false dichotomy because many non-hunters will, during periods of food shortages or maybe there's a disease on their farm, will fall back on hunting for food and money. And so this is another driver that can increase human-wildlife contact during periods of famine, for example.

Cole: Got it. So-

Peter: And-

Cole: Yes.

Peter: Many of those principles that Sagan so eloquently put out relate also to what's happening in COVID-19 where we see huge health disparities, educational disparities within this country, so different levels of exposure and different levels of susceptibility in different parts of our community. I think the one amazing thing about this infection, this disease, is the massive heterogeneities we get and the differences in how people respond to the infection, their immune system varies, the social context, which is what Sagan's talking about, and how that influence and shapes the way this disease spreads across the population.

Cole: Absolutely. The socioeconomic factors are enormous, whether we're talking about Africa or the United States of America or which virus or which infection we're talking about. Maciej, what's your take on all this?

Maciej: Well, on the spillover part, I'll relate it to the system that I've worked with most, which is avian influenza virus. I can just give the listeners another example of an environment that you need to be able to just look at in front of you, understand, study for a number of years to get a bit of a picture of how avian influenza viruses jump from mainly chickens and ducks into humans. This mainly occurs in Southeast Asia and East Asia a little bit, in South Asia and Egypt also, but Southeast Asia ... Vietnam, Thailand, Cambodia, Laos, Indonesia have been the main countries where avian influenza viruses have crossed from poultry to humans. And the environment is really millions of small holder poultry farms, so domestic poultry in people's houses. 10 chickens in one person's house, 50 ducks in another person's house, which is a system that's very difficult to control because people don't register ownership of a dozen ducks, something that you might have for six weeks and then decide not to raise another flock again.

But yet it's something that you need to be able to look at and control. You need to see how ducks and chickens go on to these farms and how they leave. You need to know where they go after they leave. Do they go to markets? Yes, and where are those markets? And you also need your very local animal health offices involved in all this surveillance because the department of health in the capital city isn't going to have their fingers into a million small farms. You need the regional and district level animal health offices communicating with farmers, asking if there's been any disease recently, and then putting together some sort of response plans when there are outbreaks, and those outbreaks when there's risk of transmission from poultry to humans.

Cole: Thank you for that. Yeah, yet another scene to paint the bigger picture. Wow. Where are we here with time? We're about 40 minutes into our talk. This has been fascinating. We've touched on origins, how important, ultimately, is it? Maybe it's too late to ever map out the ultimate origins of SARS-CoV-2, but maybe we don't have to in order to do better moving forward. Maybe we need to broaden our lens internationally to move forward. How much international cooperation do you folks experience when we're trying to map out all these different factors? It would seem to me you'd need a lot of different people with a lot of different skillsets all working together from the same playbook in order to put this map together and make this early warning system, perhaps. Give us some hope here. How's the international scientific community doing with that, and how can we make it stronger and more resilient moving forward?

Peter: You bring up two really important points there. One of this is that you need an interdisciplinary team to be able to do this, and that must include everybody from social scientists to immunologists and virologists. So in our BatOneHealth team where we're looking at spillover from bats ... and we've been working on it for, I guess, 10, 12 years now ... we have 40 PIs in our grants looking at this because we have people from every walk of life, including the people who are producing new novel vaccines, et cetera, et cetera. So I think an interdisciplinary approach is absolutely essential if you're going to get to grips with this.

Your second component is that you do need to be involved with the people in the places where this is taking place. Sagan's beautiful example of that, what she's doing in Nigeria ... I find it really gratifying to work with scientists in different parts of the country, and you really have to be there working with them, working with the local people to really understand the natural history of what's taking place. I mean, you can put all your samples and everything to one side. Just go out there and spend time in the villages talking to people. Start catching the animals, start talking to people about their contacts, and then you say, "Okay, I think I understand what's taking place here. Now I just have to be able to show it. What data do I need and how are we going to be able to do that?"

That does mean collecting samples of virus, and then moving those virus samples between one country to this country is extremely difficult because of the legislation and the restrictions on you. So sometimes you have to set up a whole new lab, as we have done in East Africa, for example, where we do all our bushmeat work. We do all the analysis there in the lab. We build a whole community of researchers, get that funding, just be able to make sure we can get these things going. It's not easy. It's complex and there's always difficulty about the semantics of it. If I wasn't on this call, I would be arguing with some of my other colleagues, and much of that discussion comes down because they see their sides and don't quite see what you're referring to and why you think that's important. So there's always this case of trying to embrace it, but hell, that's good fun.

Cole: Excellent.

Sagan: I agree. I think these interdisciplinary teams are so important. In addition to people working within their own disciplines, having people like ourselves, who I think all really appreciate the value of different disciplines and can work at least a little bit in between disciplines and try to facilitate that communication because a lot of ... An interdisciplinary team doesn't do much good if everyone's just going to go and write their own papers and not communicate about how they can really inform each other. I think that that, in my experience, has been the most challenging and the most rewarding part of it, is trying to inform each other's study design and also use the results together because there's this tendency to have these great teams but then to go on and publish [inaudible 00:38:25] papers anyway. And so that is really rewarding.

Then I think also following what Peter was saying is that working with local people not only to understand your system, but when you're trying to develop solutions and implement local-based or broad scale policies that will trickle down to a rural village in Africa or somewhere in Australia or a wet market in China, there's these barriers that we may not be able to see to behavior change in these areas. So working in a participatory way with the people that are at the forefront of that human-animal interface to know if your intervention could even be successful ... I always say that the most promising intervention that a model produces ... it may actually be the fifth best intervention that is the best intervention, because that's the one that is actually implementable on the ground and will be accepted within governments or by individuals. And so an intervention that is conceived in a laboratory or behind a computer doesn't do much good if there's really big barriers to people on the ground.

A tangible example of this is this idea that we keep coming back to of food security. In the Lassa system, there might be a win-win between food security and rodent control because if you control rodents, they're major ecological competitors with humans. They're eating our food in agricultural settings and in the household setting, so there's actually ... people are motivated to control rodents. But if you tell them to stop hunting, as my colleague Lina Moses says, the only thing that telling somebody to stop hunting a rodent does, or stop eating rodents, is change their answer from yes to no on a survey. When they go against what somebody wants to do and their motivations and benefits are co-benefits of these interventions are really, I think, important to consider to making them effective.

Peter: Cole, of course both Maciej and Sagan are appointments that came through The Huck Institutes and they are interdisciplinary people. That's why they were brought here.

Cole: Absolutely. Now, we just need The Huck to help to transform the global scientific effort and see more of that spread everywhere. It occurs to me that perhaps we don't yet have in global society ... as we look at the World Health Organization doing its best to do what it can, which is ostensibly the nexus point for the global health community, one would think, right? And so if you ever were to be able to put together an early warning system ... I'll keep saying it because that's what keeps coming into my head as you talk about all the different pieces ... That if the community could evolve the way that singular cells become a multicellular organism. Life evolves to a higher level.

Could the scientific effort evolve to a higher level like we're trying to do at The Huck by bringing the disciplines together, the international community, the social, the fieldwork, the lab work? All these different pieces ... There's not really anybody who would commission such a early warning system unless we had buy in from the international community. Do you think that politicians and people holding the purse strings internationally could be motivated to put all their money together and put some policies in play that could help to map this global early warning system that could then be deployed, as we're talking about, with the right principles to the different countries and the different regions, bioregions, et cetera? Does that sound like a pipe dream, or do you think we could get there?

Maciej: I don't think it's a pipe dream. I mean, I think WHO is the right organization to start something like this, and USAID started something like this about a dozen years ago. It's a tens of billions of dollars operation just to get started, so you do need it to get started at these very high levels. But you do need a buy in in interdisciplinary collaboration, as Sagan and Pete outlined in the way that their collaborations worked. But again, this is possible through large organizations like national governments and WHO. And after you've set up these interdisciplinary teams, the next thing you need is data. When you start, you have none of it, and then you spend a decade putting together lots of it.

One difference, for example, between coronavirus and avian influenza is that the avian influenza community, over 20 years, put together an enormous bank of avian influenza genomes, spacial databases of local farms where outbreaks had been occurring. All of this was made available slowly ... some quickly ... through partnerships and these types of collaborations that were sometimes national but sometimes international and at a UN or WHO level. For coronavirus, we have nothing like this, and actually, any chance of putting it together quickly took a hit this spring because in March and April, we sort of alienated the Chinese government and didn't exactly invite them into future scientific collaborations. We instead started blaming them for this outbreak.

I imagine for Pete and Sagan, for the systems that you work in, I imagine they're in different stages of development where you either do have enough local data to start putting together a mini surveillance system in some region, or maybe you're still a decade away because it's a disease system that requires a billion dollars of funding just to get the teams in place and just to collect all the data.

Cole: That's like one fighter jet, $10 billion. It's not even a fighter jet. Anyway, go ahead.

Peter: The irony was, we approached our funders and said, "We believe we should be looking at these coronaviruses in bats and we should be doing this sampling," and they told us, "No, no, no. You shouldn't be doing that." With hindsight, we're actually having the samples we've banked looked at for betacoronaviruses.

Peter: Anyway, I want to go back to your couple of points there, and I think Maciej brought up some of the very important points. To my mind, WHO failed very badly during this outbreak. They really should have acted faster. They should have stopped movement of people. They should have consolidated this much earlier on than they did. I mean, by early January, I was convinced that this was going to go pandemic. And I think some of that failure also sits particularly with CDC and China. They should have been acting. And it all revolves around the fact that we're talking ... It's the politics of SARS that China having already had a SARS outbreak, nobody really wanted to say this was a SARS virus because of the political results of that. That was a major issue.

If you think back to SARS-CoV-1, the WHO did a remarkably good job, and the person who led that was David Heymann, an ex-Penn State alum. David was the assistant director. He stopped the movement of people coming out of China and Hong Kong and Singapore at that time and stopped a pandemic. Now, it may never have taken place because as Maciej said, transmission was different. It's a different virus. But I do think that David's actions ... And he was told by the director general that ... and David told me this personally ... that, "If this works, then WHO will look great. If this doesn't work, you're out of a job." So that sort of level of support and the politics involved is really ghastly.

Maciej brought up this whole point about the data, and that's something that David Relman also brought up, that what we really need are easy access, rapid access to the data so that multiple people can work on those data and be able to do that in a reasonable way and do that fast and effectively. I think the science community ... As Maciej said, we did it with influenza and I think we should be doing it with a whole pile of emerging diseases. The politics is ghastly, and of course, the Trump administration stopped the pandemic committee that Obama and people had endorsed and supported during the time, and that was a real catastrophe as far as this country is concerned.

Peter: As I said back in early January, I was saying to my colleagues here and other universities, "This is going to go pandemic. You've got to do something about this." Countries like the UK could have stopped it coming in. I think if Trump had acted at the right time, he could have stopped it coming to this country. We could have taken action. We could have stopped it being as serious as it is. And certainly, as I said, [inaudible 00:47:43] New Zealand come out with probably a B-plus, maybe an A-minus, while most of the other countries are Ds and Fs, I think, when it comes down to the results. So I think the scientists could help lead us out of this, but I worry about the politics. The politics in COVID-19 have just been dreadful.

Maciej: I think Pete's right about the politics being difficult and ghastly. I just want to present the counter opinion to how good of a job WHO did, just for the listeners. I won't support either one. But the worst example is often given in China's response to the SARS1 outbreak, which started presenting with unusual cases of undiagnosable pneumonia in October 2002, but there weren't any cases that were described internationally until February of 2003. So for four months, you had circulation in Guangdong Province with essentially zero information coming out except some news trickles that were then denied and pulled back and redacted.

Then the positive example is always shown as China's response to the 2013 H7N9 avian influenza outbreaks. The first patients with unusual pneumonia appeared in the third week of February 2013. On March 31st, five weeks later, China had everything characterized and published and submitted to The New England Journal of Medicine. That's a rapid and open and successful response, and the outbreak was stopped, but it took five weeks. And I don't think the Chinese CDC knew on December 30th that that five-week window to get everything together, to sequence the virus, to develop the diagnostics, and to begin the control procedures ... I don't think they knew that that five-week window wouldn't be enough.

So December 30th was the point at which they realized something needed to be done. January 10th was the day that the sequence was made available and diagnostics could be made. January 13th, you had a case in Thailand. January 15th, you had a case in Japan. January 17th, you had a case in Korea. In those 17 to 19 days, it just got away from them. I think we all knew at that point that it was risky, and I think they'd realized that they'd failed, but how much blame we should put on this response not being fast enough, that's subjective. I mean, I wouldn't put too much blame either on China, CDC, or WHO as if we'd expected them to know that it needed to be done in those two weeks.

Peter: With hindsight, what should we and what could we have done? And I don't just mean us Americans or us, the Western community, but the whole world should have done. What should we have been doing at that time? I think if we'd had our act together, we could have done it. But I do appreciate your point, and when there is an outbreak, it's ghastly because some people are saying, "This is not transmissible between people," and with hindsight, of course, we knew it was. But at the time, they were saying, "We don't believe this is human-to-human transmission going on here." So-

Maciej: Thank you. Thank you, Pete. There's an answer to this question. WHO's big mistake in 2003 and in 2009 with the swine flu pandemic was pushing forward the notion that airport closures don't work. The reason they put forward the, "Airplane closures don't work," story is that they knew or guessed correctly that no country would be able to close their incoming travel sufficiently to prevent the swine flu pandemic or the SARS outbreak from taking hold in a small group of people. They thought it was a total waste of effort. Airport closures, of course, do work, if you close everything completely and don't let anybody in. But in both '03 and '09, WHO just viewed that as a completely unworkable strategy.

But by the third week of January when they noticed that it was spreading out of Hubei and into other provinces in China, and when they noticed that they had single digit of cases in other countries, this was the moment to reverse that one piece of advice and essentially to tell the first two countries, Italy and South Korea, that experienced major epidemics ... This was the moment to tell other countries to close their airports and to stop all travel for three to four weeks and that could have done it.

Peter: So I think the pressure, or the pressure that David Heymann always says, is the pressure on you is that this is going to hit the business world.

Peter: When you saw when they closed the airports, when they closed the East to West, you saw it. You saw a blip in the business productivity, and then it came back relatively fast. But it's going to take a while for this one to come back.

Cole: Yeah. We talk about this on this podcast. It's sort of like it's your money or your life, right? And where are our values, and what's more important? Human health and well-being or the almighty dollar? The fact that when our government just whipped up a couple trillion dollars and handed it out kind of points to the absurdity of this imaginary money system we have anyway, and I think we need to get more creative about how we think about money because it's all a social construct anyway.

Humans are real, food is real, houses are real, all these things are real, medicine's real. Money is this imaginary exchange system that human beings created to exchange things, and so if we can bring forward new principles, new values, if we can value health and well-being more, and kindness, and international cooperation more, and competition, and beat the other guy less, and, "We need to be the first ..." If we can start to make that change in our consciousness, perhaps that will be the turning point that will allow us to work together more and do things like we're talking about, the whole international community working together to see the big picture, to put the pieces together for everybody's well-being.

So that's our hope. That's what we try to do in this podcast, is to put forward some of these new ideas and raise the consciousness of the people in our own little way to help move us in that direction. I thank all of you for everything you're doing to help move science in that direction.

So we're just about at the end of our time together. It's been a fascinating conversation. Does anybody have any sort of wrap-up comments, last things you'd like to share with our listeners and our viewers? Maciej, do you have some last thoughts?

Maciej: Yeah. I'll just say about the origins of SARS-CoV-2, we're not quite there yet in understanding which bat populations it came from or how recently it may have jumped from bat populations to human populations. Probably what we're looking at in the next 5 to 10 years is a lot more sampling of wild bat populations in China and sort of filling out the phylogenetic tree of betacoronaviruses and sarbecoviruses. As we get viruses that are closer and closer to the one that jumped over into humans at the end of 2019, we'll have a good picture of how that spillover occurred and where it could have occurred from.

Cole: Thank you. Sagan, what about you? Any last thoughts for our folks?

Sagan: I keep thinking back to your question of if we can predict spillover and, based on our conversation and just observing the political climate, it's not only, I think, our ability to predict, but our ability to implement the changes that we need to implement in order to curb spillover. I think that that's really ... I mean, as scientists, as we're working really hard in these interdisciplinary teams, translating the science into policy is a gap that I think is clear to all of us and would really help. From my perspective, it's very clear where human behavior comes into play here with increase in spillover in human-dominated landscapes, engagement in wildlife trade. We know these behaviors are risky and result in spillover, but it's about translating that science into policy that can really help us move forward as we continue to elucidate the origins of some of these viruses.

Cole: Absolutely. Thank you. And Peter, do you want to bring us home with some last thoughts and comments?

Peter: While I am, of course, a scientist and a naturalist, I do believe very strongly that what we're looking at is an environmental issue here. This is taking place as a consequence of massive habitat destruction, loss of biodiversity. We know this is immensely important in buffering infectious diseases in the emerging disease scenario. So I feel very strongly that we have to really think about this in an environmental context, which might involve stopping habitat destruction, might involve large parts of the world changing their diet and the way we actually see the world. So I think this is a wake-up call, and I think it's about time we woke up.

Cole: Well said. Well, again, thank all three of you for being on The Symbiotic Podcast today. It's been a fascinating and informative conversation. I thank you all for the good work you're doing to help advance science globally, to help contribute to the evolution of science, and hopefully to a healthier and more equitable and more balanced world where we're living more in harmony with nature and one another and creating a world where we can all do better together. So thanks again. Everybody out there, thanks for listening and don't stop coevolving.