Michelle Moyal (Host): Hello everyone and welcome to the Cornell Veterinary Podcast where we do a deep dive into all the discovery, care and learning that happens at Cornell University's College of Veterinary Medicine. I am your host, visiting assistant clinical professor, Dr. Michelle Moyal, and might I add, fabulous Purina veterinarian. And now that we have reached December, I am the embracer of the fabulous holiday sweater. If you can't see this, everyone, and you're listening, I have on dare I say a medium ugly, not super ugly Cornell festive sweater. So, thank you. I'm so glad we got to discuss that first.

Okay. My guest today is Dr. Ana Bento, Assistant Professor in the Department of Public and Ecosystem Health. Dr. Bento is a quantitative disease ecologist-- don't worry everyone, you know I'm going to ask her the details about this-- who uses machine learning and mathematical models-- excuse me, I just passed out because it involved a lot of math-- to identify the evolutionary demographic and environmental causes of disease spread in humans and animals, oh, and how data-driven modeling can prevent future pandemics. Wow, that's a lot. We definitely want to hear more about this.

She earned her PhD in ecology and evolution at Imperial College London, and was a postdoctoral researcher at the University of Georgia and faculty at Indiana University before joining us at Cornell. During the COVID-19 pandemic, she took an extended sabbatical from her faculty position to lead a computational outbreak response lab at the Rockefeller Foundation's Pandemic Prevention Institute. Most people go on sabbatical, they go on vacation. That's not what happened here. She focused on surveillance and modeling in low and middle income countries. We need to know more about that. Welcome to the show, Dr. Bento.

Ana Bento, PhD: Thank you so much. Call me Ana. Michelle, it's really a pleasure to be here. And like you, I'm also using festive colors because it's December.

Host: Yes. I love it. She's wearing a beautiful red sweater, everyone. I'm here for it, you know, I'm here for the fashion. I also try to do a little bit of makeup today. Makeup artists, if you happen to be listening, because you're also into science, don't come at me with comments. It was a very sad, sad attempt.

Ana Bento, PhD: Or you invite them over and we all do a tutorial.

Host: Yes, I love this. I love this. I challenge you all. We could talk science at the same time. And then if you can allow me to master smokey eye, I would greatly appreciate it. Okay. Okay. So, Ana, it was a lot of stuff in your intro, but my guests know I always like to know an origin story, right? Just like a good movie. Can you tell us like where did you grow up and what brought you to Cornell?

Ana Bento, PhD: Yep. So, I grew up a little bit of all over. I'm from Portugal, which is a country in Europe, for those of you don't know, because it's a tiny country in Europe. But I traveled a lot as a kid. So, I spent some time in Mozambique and Angola, which are countries in Africa, and in Brazil as well. And so, I traveled quite a lot as a kid. And when it came to go to university, I didn't really want to stay in Portugal because I was so used to like not being in Portugal that I moved to the UK to do my undergraduate. So, I kind of grew up a little bit everywhere. And so, I always pause when people ask me where I grew up or where I'm from because I like to believe in a very cheesy way that I'm a bit of a citizen of the world because I--

Host: Love that. Yes, love that. And being a citizen of the world includes delicious food. And I'm always on board for that. Well, that's wonderful. So after you were in Georgia, you were at Indiana University also, you were in London. So, how did you get to Ithaca?

Ana Bento, PhD: How did I end up here? Of course, I forgot to answer that bit. Oh my. So, it was kind of like my life has been kind of a series of fortunate events to, like, make it.

Host: Oh, I love that.

Ana Bento, PhD: And so, as I mentioned, I moved to the UK to do my undergrad. And I stayed there for my undergraduate, my PhD. And then, when it came to think about doing a postdoctoral work, which is the education between being a full grownup, but you kind of like finished your PhD and you're not quite ready yet, so you do a few years of research, so I moved to University of Georgia.

Host: Is it like supervised research for everyone listening who wants to do like a PhD, you don't have to do postdoc work?

Ana Bento, PhD: So, most degrees in the biological sciences always require a little extra leg of research. Is almost like--

Host: Leave it to science.

Ana Bento, PhD: Science never stops. So

Host: That's true.

Ana Bento, PhD: Exactly. So, I moved to UGA, and then I got a faculty position at Indiana University in Bloomington, which I loved. But then, I think that was in 2019. The pandemic exploded a few months later. And I got very busy, because I worked in infectious diseases, that I'm sure. And then, at some point when I was getting ready to kind of go back to Indiana after that sabbatical you mentioned, which I'm sure we'll talk about in a bit, I got asked to apply for a position in Ithaca at Cornell. And here I am.

So, it's always been kind of a little bit of an adventure of, "Let me maybe move for a few years to the U.S.. And that was 2015, and I'm here still. Let me apply for something in Ithaca, maybe it might work out." And here I am. So, it's always been a little bit of that. Cornell is a very special place, as you know. Because I work in infectious diseases and in emerging infectious diseases at that, the idea of thinking about One Health is very important. And I know you had Steve Osofsky not long ago here for--

Host: If you recall, listeners, he was our biodiplomat.

Ana Bento, PhD: Yes. Exactly. So, One Health is one of the most important concepts in emerging infectious diseases, which is this idea that you don't focus only on animal health, on human health or on the environment, but you holistically think about the whole scenario. So, it seemed like a wonderful place to come and join the faculty, to join like-minded individuals to go on adventures together, I guess.

Host: You left some areas like Georgia where the weather was warm, and here you are in Ithaca.

Ana Bento, PhD: And I did love Georgia. Georgia was an amazing place to start my U,S. adventure.

Host: Love it. And I always point this out to our listeners, if they're young, if they're older in their journey, it doesn't matter. What I very much appreciated you saying was that it was this series of events, fortunate or not, right? So, you said you applied to Ithaca. If it didn't work out, you would've gone down another path. So, I just want people to get dissuaded from their passion if one opportunity is not available to them. Trust me, there are a series of fortunate events waiting for you as well. We just have to keep chasing after them in different places.

So, I often ask because I think a lot of us as veterinarians will say, you know, we loved animals from a young age. We weren't sure if we were going to be a doctor. Some of us were very sure, right? I wasn't sure until I was older. What led you to this? What led you to this field of like disease dynamics

Ana Bento, PhD: yep. So, okay. So maybe let's back up disease dynamics, what is it?

Host: Yes. Back us up. Back us up.

Ana Bento, PhD: Disease dynamics is the study of how diseases spread, evolve over time and space, of course, and then how do they persist or not in a particular population. This can be a population of humans or of any other animals or either or even populations of plants, right? So, that's disease dynamics for our listeners.

Why I got involved into this? Again, by accident, I guess. So when I was doing my undergraduate, the first day of my Ecology 101, the equivalent of Ecology 101 in my degree, one of my favorite professors who then became my PhD advisor put up a photo of, like a photo on a slideshow of an island called St. Kilda, which is St. Kilda Archipelago in Scotland. And this is an island in the middle of the ocean, in the middle of nowhere. There's nothing around. It's so remote and so kind of deserted. There are no trees, so it's only grass. There are no carnivores. So, the top honcho of the island are sheep, these really cool neolithic, semidomesticated sheep that haven't been domesticated for over a hundred years in that island. And there's very few humans in that island as well, only the scientists that go in and study these crazy sheep.

So, I saw that photo and I said to myself, "I want to know more about this." So over the course of my degree, I convinced this professor that I wanted to do a PhD on this island, chasing sheep basically. Because I am a theoretician, right, I like math, the idea was to spend half of my year chasing sheep and actually chasing deer, but I'll get to that in a second. And then, the other half sitting in front of my computer, creating simulations, and developing theory to understand why I was observing the patterns that I was observing. So, no disease whatsoever. I was interested in understanding how the weather and their food were affecting how they were surviving harsh winters and how they were multiplying or not over the years.

Host: Right. Without human interventions essentially, right?

Ana Bento, PhD: Zero human intervention.

Host: This is a beautiful study subject because they're, like, isolated.

Ana Bento, PhD: Completely. No hunting, no intervening. It's an island where humans just go in and observe. And so, my PhD became this interesting project, I think, of trying to understand why these sheep, these populations have these booms and busts. So, some years. They multiply, and they completely invade the island. In some years, they just crush, and more than half of the population gets wiped out. I was also very interested in understanding.

In a not so far away island, another group of ungulates. So, these mammals, like sheep, deer in this case had a very similar setup. So, no carnivores, no humans, but they were not doing these booms and busts. So, that became my PhD. So, no disease whatsoever. And I did that and it was super fun and I discovered why they were so different. And you're vet so you appreciate this. It became about what they eat, when they eat it, and how their life history was so different, right? So, sheep reproduced super fast. We used to joke that they were like the James Dean, which no kids know at the time-- now, I'm aging myself-- the James Dean of the mammals, which means that they live fast and they die young. And the deer were just reproducing much later in life. So, that became like our big discovery, that it was really about how late they left their life cycle to start basically. So then, towards the end of my PhD, there was a group of scientists that joined this group of scientists that were interested sheep.

Host: Oh, I hear collaboration.

Ana Bento, PhD: Absolutely. So, yes, I guess the thing that it's important to say here is that this group of scientists were three universities working together. And it kind of spans all sorts of fields from physicists, mathematicians, biologists, microbiologists, immunologists, parasitologists. So, everybody had a role. And the idea was to really understand across these fields how processes were kind of dictating what we saw on the islands and on these sheep populations and deer population. So towards the end of my PhD, I met these immunologists and they started getting interested in nematodes, which are these worm-like parasites.

Host: Parasites. Yeah.

Ana Bento, PhD: Which are super cool in a very perverse way.

Host: You know a researcher really loves science when they say those nematodes are cool. We all do it. We all do it.

Ana Bento, PhD: They are. And then, I started collaborating with them with this idea of what makes a population vulnerable to these parasites, and are they always vulnerable or is there a need for kind of alignment of conditions? So, let's say a bad winter plus a lot of individuals in the population, so not a lot of foods. And that's kind of creating that kind of shift to a cycle of doom, right? This idea that all of a sudden all of these conditions are creating the possibility for disease to actually create an imbalance in the population. And if the parasites kind of get into a population in a good year where the winter was nice, there aren't a lot of sheep around, then actually nothing happens. So, my job was to quantify that, right? To say exactly what is the timing, how many sheep need to be around, how bad does the winter need to be for this to happen? And so, I kind of started being interested in disease, even though my PhD earlier had nothing to do with disease.

Host: She was just chasing sheep people. Just chasing the sheep.

Ana Bento, PhD: In fact, my mother used to tell her friends that my PhD, I was a glorified shepherd, because all I did was to just go up and down mountains chasing sheep, catching them, which to this day I find hilarious. But there you go.

Host: I mean, shout out to shepherds in general. We know the kind of work they do. But hearing this, I don't think we knew.

Ana Bento, PhD: We would not have these sweaters.

Host: That's correct. Your step count must have been amazing.

Ana Bento, PhD: Oh, for sure.

Host: But on top of that, I've heard so many good things and themes that we've talked about on this show just with doctors and researchers across the board, right? Like, one, as someone who now works in nutrition, you mentioning nutrition as a very important part of the cycle is very important for me, because nutrition is important in disease and in health. So, I always love to bring that up. Then, you brought up that here you are, looking at these dynamics and there's a physicist with you, right? So, I always like to talk about diversity of thought. Like, when you went to "chase the sheep", we know she was doing so much more studying, guys. But when you went to do that, did you expect to see a physicist or all these other different sciences, mathematicians, and then you end up collaborating and maybe that physicist brought forth an opinion or a viewpoint that you didn't think of and that impacted you in a positive way to do your work?

Ana Bento, PhD: Yeah, absolutely.

Host: And I love that. I love that. And that's the importance of collaboration. Like, I know we all have our focus of research, our focus of practice. But without others making us better, we can get stagnant. Maybe we miss an important thing in the cycle. And it's very cool that she's quantifying how cold a winter is to affect these animals, like things that I didn't even think you could quantify. And so, now, you have this interest. You decided that disease is an important focus, and actually like there are some diseases you really went on to study, and I will get into that. But I guess when you left your PhD or that work, what was the question you most wanted to answer when you were like, "Okay, that's it. I'm going to be a full grownup science grownup. I would love to answer this" ?

Ana Bento, PhD: Difficult question to answer because many questions were coming from that. But I guess the question that still drives me is trying to understand. So, I was saying really clever things, but I will step back. So, I think that the question that still kind of drives me is really trying to understand why are some populations more affected than others by the same pathogen.

Host: Gotcha. Yep.

Ana Bento, PhD: So, this kind of translating across different species, across different pathogens, right? Is this kind of understanding of the timing and the alignment of conditions that make something kind of emerge and then spread, right? So, those are the questions that I'm most fascinated by.

Host: Th is is so neat because we've spoken to doctors who have also worked on like in unique areas and have studied disease in different-- like we had one study, she was studying seabirds and diseases in seabirds, right? And how it affected one population over the other. And here you are doing-- I'm going to say not something similar, but you are also looking into disease emergence, but in a completely different way and using different modalities, which is very exciting. So for all our math lovers, I think that this is very exciting. How does math figure into what you do? When you say-- I wrote this. So, I wrote this because I always creep on websites of who I interview, and it says you use mathematical and computer modeling. So, what does that mean in your position?

Ana Bento, PhD: Yeah. So if you think about a season of a particular disease, right? So for our listeners, let's think about flu because it's the season of flu, right?

Host: It sure is.

Ana Bento, PhD: So, one individual gets the flu, right? And then, they may have the opportunity to transmit to other individuals in the same population, right? So, mathematical models are a way to kind of dissect that. So, the moment of somebody becoming infected, and then that kind of flow of one person infecting another person. So, that's the timing. And then, from that second person to infect another person, that's another timing, which we call chain of transmission. So, mathematical models or equations can actually translate those very complex biological processes of transmitting a disease from one person to another into equations that then allow us to define those timings, right? The timing of becoming infected, the timing of infection, or the number of individuals that one person can infect and so on, right? So, the models are a way of kind of simplifying the world that we live in, right? The simulations or computer models are my very creepy way of creating an infection without killing or infecting anyone.

Host: Sure. A little pretend infection. Gotcha.

Ana Bento, PhD: Exactly. So, I can actually study that, right, in this kind of in silico or in these artificial settings, in a way that I can then design interventions to either mitigate or stop an infection or design policies or design interventions to actually prevent something from happening to begin with. So, that's where the pandemic prevention comes in. So, it really just is a way of simplifying our very complex protocols.

Host: Yeah, that's really cool. Because when I think about things-- and definitely correct me if I'm wrong-- before we were able to do mathematical models like this, maybe the only research we could do was experimentally infecting animals or organisms with these infectious pathogens. And then, watching it spread, which is very timely. And then, obviously, we have these other beings. I'm not commenting on the U.S.e of animals in science. I'm just commenting on this almost like in a sustainable way. a very neat way to look at it. That's very cool.

And so, now, I heard-- and by heard, I mean, I stalked and wrote down-- that you received something called the Atkinson Impact Award to understand the dynamics and patterns of the spread of zika and dengue. Those are not small diseases, everyone. She can tell us some little bits about it. But could you tell us about this project and what you're hoping to learn from it, What you did learn?

Ana Bento, PhD: Yes, absolutely. So now, I was giving you an example of the flu, which is a respiratory disease, which means that I can directly infect Michelle. Zika and dengue are examples of diseases that require a vector, so require, in this case, a mosquito to bite me, get infected, and bite Michelle. So, that is the kind of very quick crash course on vector--

Host: Yep. You have have the mosquito in order for me to get that from you, for everyone listening.

Ana Bento, PhD: Yeah. So, zika and dengue are these mosquito-borne diseases. For those of you who are very into mosquitoes, they're vectorized by Aedes aegypti, which is one of the most prevalent mosquitoes in the Americas. And dengue, unlike Zika, continues to be a problem every year, and it's becoming a bigger problem. In the past four years, three years, the number of cases has increased quite a lot. And it kills millions of people every year.

Host: Millions of people every year?

Ana Bento, PhD: Every year, in the Americas. So, zika is slightly different, even though it's vectorized by the same mosquito in that it had a big outbreak in 2016, '17. And although there are still cases in the Americas, it never really became a big problem again. So, we still have cases in Brazil. We still have cases in Columbia. But we haven't had a big outbreak like that.

So, this project that I was awarded, this Atkinson Award for, is trying to ask two questions. One of them is, can we understand whether Zika, this one that had an outbreak about 10 years ago, might have a comeback? And can we understand what are the necessary and sufficient conditions for Dengue, which is endemic in the Americas, to become endemic in other parts of the world? So, this can be North America, Europe, or countries in Asia where it has not been able to spread yet. So, those are the two main questions that this project is looking at.

And the fun bit is that, I guess. Within this horrible theme that I'm studying, is that I get to spend a lot of time in Brazil with my colleagues in the fields, that are doing a lot of sampling with mosquitoes.

Host: May I ask, are you like in a jungle? Like, what can our listeners picture? Where are you collecting these? I say jungle, but mosquitoes are everywhere. Obviously, I'm like playing into certain types here, but where are you?

Ana Bento, PhD: Where am I? So, a Aedes aegypti are mostly an urban mosquito. So, mostly in urban settings.

Host: So urban mosquito. I'm joking about jungles, but like I come from a big city, it's not easy to control infestations of all sorts of bugs.

Ana Bento, PhD: Absolutely. Yes.

Host: Small mammals. Lots of people, small space.

Ana Bento, PhD: Yeah. However, I do work with forest-dwelling mosquitoes, not jungle-dwelling mosquitoes for another disease called yellow fever to study these same ideas as well. So, you mentioned urban settings and you being a city person, one of the things that we're trying to understand is precisely what are those urban setting conditions? These conditions that allow for mosquitoes to go back to terms that I've used before their life cycle, the conditions that allow for larvae, which is like the young mosquito to develop into adult form, which is the mosquito that goes around and bites people and potentially transmits the disease. So, those are the types of questions that we're interested in to understand the role of the mosquito and the context of their lifecycle, meaning the conditions that allow for the mosquito to successfully go from larvae to adult and then become a problem. And then, the conditions that affect humans, meaning their behavior. So for instance, dengue now has a vaccine. So, what leads a human to take the vaccine or not, and how that affects the layer of transmission in the humans. And then, the environment, which is kind of what are the temperature, humidity, and precipitation, so rain, conditions that dictate how early in the year does the season start and how long does the favorable season for transmission of dengue in this case, zika as well, lasts. And then, this idea of if weather keeps changing and we know that it is changing whether these conditions might become permissible elsewhere. So, that is the idea behind trying to see whether we understand when dengue might become a problem in Florida, in Texas, without relying on cases that are coming from the outside.

And the same with Zika, what are the conditions that allow for Zika to come back? So, it always relies on this kind of approach of complex systems, which is these different layers, right? The environment, the vector, the human and the pathogen, how do they align and what are these conditions that allow for something to explode and continue spreading in time and in space.

Host: This is blowing my mind. There are so many factors you have to look at. Where do you start? Do you have a starting point? Do you say we always start with the human or we always start with weather or because of mathematical modeling you can do more than one? Is there a starting point?

Ana Bento, PhD: The starting point depends on two things, on the disease or on the pathogen, right? So, is it respiratory? Is it vectored? And then, we also think about what is the question. So the pathogen and the question, if the question is how fast are they spreading? We might start with the number of cases in humans or the number of cases in not humans, because it depends on whatever population you're interested in. So, I'll give you the example of one of my favorite diseases, yellow fever.

Host: She has a favorite disease. Everbody, you heard that.

Ana Bento, PhD: I do.

Host: We all do, whether like curable, non-curable, like we all have something that really fascinates us. I don't want anybody to be like, why would anybody think of a disease as a favorite thing? But really, it's about kind of the everything behind it that lends to us wanting to study, wanting to research them.

Ana Bento, PhD: That's right.

Host: Okay. So, tell us about your favorite.

Ana Bento, PhD: Favorite disease is yellow fever, also a mosquito-borne disease. But yellow fever--

Host: This supports my dislike of mosquitoes, by the way.

Ana Bento, PhD: Oh, yes. I really am not a fan of mosquitoes, although I detest ticks more.

Host: And they love me.

Ana Bento, PhD: I hate ticks more.

Host: Yeah. Oh, okay. That's valid. She hates ticks more. Got it. Okay. Okay. Sorry. Go ahead.

Ana Bento, PhD: So, I'm going to tell you a little bit about my favorite disease, yellow fever, that is caused by a yellow fever virus in a very imaginative way, and is caused, again, by a mosquito. But the fun bit about yellow fever is it has two cycles. One cycle that does not affect humans at all, and is completely kind of independent of humans. And it focuses on non-human primates, and what I mean by this is different types of monkeys, titi monkeys, Capuchin Monkeys, marmosets, howler monkeys, really cute huggable monkeys.

Host: And all sorts of cute monkeys.

Ana Bento, PhD: Very cute. And these are forest-dwelling monkeys that occasionally kind of get into contact with humans. And the idea behind this is to understand how does disease persist in this population. And all of a sudden becomes less so of a problem of pandemic prevention, but an angle of trying to understand conservation of these populations because a lot of these monkeys are endangered in Brazil. So, that's how I started getting kind of involved in this project. So here, we start by understanding what populations of monkeys there are. Where do they live? Are the numbers changing over time? Where are the mosquitoes that affect this wildlife cycle of yellow fever, like the different types of mosquitoes, where they are, what's the seasonality? How many bites per day? Do they fly very far? Are they faithful to a particular population? And I'll get to explain why I'm saying these words.

Host: This is really interesting. Didn't even think about that.

Ana Bento, PhD: So, really thinking just on that side. So, those are the kinds of questions we ask or the kinds of data we start with. And then, there's a connection to the human cycle, which is actually quite dependent on the wildlife cycle. So occasionally, there's a kind of an interface, right? A connection between these non-human primates, these monkeys and humans. Why? Because humans are deforesting, humans are encroaching in habitats that they shouldn't be in, right? So, all sorts of behavioral things we can get to later.

And then, what happens is that because this is a vector-borne mosquito, and it's kind of fun, right? The forest-dwelling mosquito may bite the monkey. The monkey goes around areas that are neither too forested nor to urban, and can encounter mosquitoes that bite humans, the Aedes aegypti mosquitoes, and then the mosquito bites the monkey. And the monkey then bites a human and an outbreak can start, so two very different cycles that are kind of interconnected by these different factors.

Once we are looking at the human cycle, we start by looking at how many cases in humans, are humans getting vaccinated? When are they getting vaccinated? How is the population over time protected? How many outbreaks were there before? So then, it's no longer a conservation problem, but actually a public health problem. So, different questions, different data, different models, right? So, then, the project that we are very interested in is precisely to try and connect entomologists, primatologists on that conservation side with epidemiologists and disease ecologist like me, and sociologists and even psychologists at this point with the public health side to really understand not just this potential of spillover, meaning jump of a pathogen from one species to humans, but also spillback of the pathogen back from humans to these monkey populations. So then, because it's a big problem. We start stacking up the different types of data, and we start building a model to understand how these diseases are spreading in these different populations over time and at the different demographic groups of these populations, meaning different agents to understand how immune the populations might be, because that affects on how likely this pathogen might be able to be successful, right? Should it jump one way or the other way?

So, that's why mathematical models are kind of easy in a way, right? Because they take up all of these crazy amount of information, right? It is, right? It's easy to do a model in a computer than it is to go into the field, catch mosquitoes, or catch monkeys, or convince people to get vaccinated, right?

Host: I am shaking my head at her. The thought of me trying to-- we thought her chasing sheep was interesting, me trying to catch a monkey or a mosquito, I'm literally just laughing at myself.

Ana Bento, PhD: Right? It's fun. So, this morning I was having a conversation with my entomologist colleague who was deploying these big balloons to actually sample mosquitoes in the air in these different environments. And my job is the simple one, which is once you get this data, to estimate how far are these mosquitoes flying, are they kind of staying in the same place, and trying to understand how many mosquitoes we actually need to have in a particular place to potentially cause an outbreak, how many do they need to be infected in the mosquito population to potentially cause an outbreak? So, my life is the easiest part, right? Like, what I do is just that teensy bit, like, just to make it a little bit more practical.

Host: We say that, but the far reaching effects are just wild hearing about this. This truly is One Health work. Wow. And so, hearing all of this about potential outbreaks and how the stars have to align for certain things to happen and outbreaks to happen, what was it like going through the COVID pandemic? I mean, obviously I know, and I mentioned in the beginning and you can point it out and tell us why you left and took your sabbatical to do this important work. So, did living through an actual pandemic change your point of view on what you do?

Ana Bento, PhD: Yes.

Host: You're like, "Yes, this is why I study what I study."

Ana Bento, PhD: So, I think that everybody that lived through the pandemic, one, remembers when the pandemic was declared; two, remembers how they had to change their lives dramatically, either because they were able to stay at home or because they were not able to stay at home, but they needed to get protected. And it really was an event that has repercussions that we are still living through. So, it has changed a lot, not just from a scientific point of view, but also from a personal point of view. And I think that most people will say the same, right? That the pandemic has affected them in some way.

From a scientific point of view, which is why I'm here today, it really kind of allowed me to start thinking about problems, not just from the biological kind of point of view, but start thinking about how I bring in behavior into my models, right? So, once SARS-CoV-2 moved from, whatever reservoir species that we're still truly trying to understand, onto humans, but that's a podcast for another day, and maybe I'm not the right person for that. I would have another colleague come for that. But once it kind of started spreading in the population, initially all of the work that I and colleagues were doing were in two kind of camps.

One was trying to understand how fast we could kind of control it, which turned out to be a wrong approach. And the other one was if it's evolving, what's the consequence of that, which is a good approach. What I started becoming obsessed with was how can we incorporate behavior into these models to try and understand precisely how fast something can spread, and can we actually develop interventions that are behavioral in their nature to understand how once, for instance, a shut down or forcing people to stay home, once they go back to their normal lives, how can we actually utilize the information on behavior to make sure that we don't have a bounce back, right? Because early on the data we're telling us things like, if you say on a Monday that you're going to enforce a closing of everything, bars, supermarkets, schools, that people were doing this really interesting behavior, which was doing everything, that they could super fast because they would probably stay two weeks, three weeks, four weeks, without doing all of the things that probably they hadn't done in six months, but all of a sudden they wanted to do--

Host: Right. Like, they wouldn't have done it normally. Like, there's no need maybe to go to the bar for three months. But all of a sudden when someone said, "You cannot go to the bar," they were like, "Let me go to the bar quick."

Ana Bento, PhD: Exactly. So, we saw this really interesting, very interesting thing, which was before a lockdown, there was a lot of interesting behavioral activity that we weren't seeing, that was not kind of in keeping with the past seasons because we had historical data. So, we knew more or less people are predictable. And we knew that they were rushing to contact. And during the lockdown, then we were able to appreciate that even though people were reducing their contacts, there was a lot of transmission that happened just before that.

Host: Wow, this is wild. So in the attempt to shut everything down and stop this pandemic, we behaviorally impacted the group, and then they raced out. And then, inadvertently, we increased contact in that period.

Ana Bento, PhD: It's crazy, right? Which means that, if you don't account for that evolution of behavior, you can never understand or predict that outcome, right? So then, at the end of a lockdown, we would also see people rushing to go back and do the things that they hadn't done for whatever many days or weeks, depending on the country.

Host: They want to be normal, right?

Ana Bento, PhD: That's right.

Host: They want to resume life. I get that. Yeah.

Ana Bento, PhD: So, the fun thing about this as well, and maybe just fun for me is that, for instance, we also saw that in cities, in urban settings, the normal behavior, the baseline behavior from previous years didn't return as fast as it did in more rural areas, which is again, something that you would not expect. And so, incorporating this kind of information that perhaps being in a more remote setting means that you actually do need to go back to your previous behavior. Otherwise, you might not be able to find your food, or you need to like travel far to go to your post office, any sort of like more remote area activity.

Humans in these kinds of settings returned back immediately to their pre lockdown conditions. But in urban settings, we did not see that. Again, this kind of information of behaving evolving over time became my obsession, right? And so, that actually opened a very different type of research avenue that I didn't have before, which is how do I now add one more layer into my already complex models to understand how we can allow for behavior to evolve over time? Meaning if I know that there are 10 cases of flu today in my neighborhood, how do I model that choice of me staying home or not staying home knowing that perhaps I can make that decision. But some of my neighbors, for instance, cannot, my neighbor has a job that regardless of the condition they need to go out, right? So, that kind of complexity.

And so, I added one more type of modeling and one more type of colleague in my universe, which was economics. So now, I collaborate with economists to really understand that kind of decision of do I go out and make money so I can spend money? Or do I stay home, not make money, meaning that I cannot spend money? So, this kind of willingness to do something and that allows us to track behavior dynamically in our transmission models in a way that, before the pandemic, I was not really thinking about in a way that I was willing to do it. So, my husband jokes that during the first year of the pandemic, while people were learning how to bake sourdough, I was learning economics.

Host: Guilty. But I was banana bread. It's fine.

Ana Bento, PhD: Oh, even better.

Host: You were learning economics.

Ana Bento, PhD: Yes. But I was benefiting from banana breads and sourdough from my friends. So, everybody wins.

Host: But like in turn, I feel like if you keep doing these models and you can keep learning, then you could also impact governmental policy. Like, the government doesn't want to shut things down, right? It was literally we didn't know what was happening. We were frightened. This disease appeared very contagious, right? So, the hope here is that really you can impact-- I hope nothing like this ever happens again-- but that maybe this can influence policy so then we don't have to do things, and then we don't lose money and we can go spend this like beautiful circle of sustainability as far as like helping people to keep jobs and support the economy.

And so, I think this is a tough question. There are a lot of things going on in the world right now. And there are a lot of people and there's a lot of-- we said it, there are a lot of layers to the onion and the models that you create. Are we doing enough? Is there something to do to prevent pandemics? Are they inevitable? Is it just going to happen? I mean, we know climate change is happening. We know there will be probably more mosquitoes and more illnesses.

Ana Bento, PhD: Yeah.

Host: I guess, what do we do? She'll answer that. It'll be easy. There will be no other pandemics. You heard it here on the podcast.

Ana Bento, PhD: All right. So, there will be other pandemics. Kind of the million-dollar question is the when and the where. So, we had SARS-CoV-2 in 2019, 2020. Only affected humans in 2020 mostly, right? But it really did kind of emerge in 2019. Before that, we had another SARS CoV, so another SARS virus in 2003 in that didn't quite make it as a true epidemic.

Host: Yes. I remember hearing about that on the news though, when I was younger. I remember it being seemingly because it didn't affect us, so there was no impact on us in the U.S., so we just kind of heard it.

Ana Bento, PhD: Yeah. The other one that I think will maybe answer some of your question is swine flu in 2009 emerged in Mexico. And nobody thought a respiratory disease of a pandemic potential would emerge in the Americas. Because the prediction is that, because of these alignment of factors, that it tends to emerge from Asia for all sorts of behavioral, like interface with animals and humans, different types of practices, agricultural or life market practices. The idea is that it tends to be looked at in Asian countries or Asian settings. So in 2009, nobody was looking at Mexico. And so, it actually spread, like SARS-CoV-2, kind of cryptically, so like invisibly for a long time before it became a massive problem.

So, the key to potentially preventing these things is really trying to understand how you can effectively create surveillance in different parts of the world, thinking of the different types of viruses, because normally pandemics are mostly caused by viruses, where they are, what species should we look at. So, it's not really thinking about where are we going to prevent them by focusing on humans. But actually, again, to go back to our One Health theme, thinking about what kind of species should we monitor, what are the potential reservoirs of these viruses that have the potential to spread very fast? And then, thinking about what kinds of, surveillance systems we set up to look at this. So, thinking about wastewater surveillance, is an interesting one that is still developing. So, it's not quite there yet, but it can give you an idea of a green light, a red light, like presence, absence of something. So, it doesn't tell you how much there is, but it can tell you something.

Host: And we've talked about this on this podcast before, even with regards to COVID surveillance in wastewater systems,

Ana Bento, PhD: Yeah.

Host: pretty. Fascinating.

Ana Bento, PhD: So, thinking about the different types of data you can collect to start building that layering that we've been kind of discussing today of each layer provides you some information, right? And then, if you build these different types of layers, then you can actually collectively start thinking about can we have an early warning signal? Meaning a signal before something is about to appear. And we're not there yet, not even close because our planet is large. There's many places of interest. And as you said very well earlier, with climate change, with deforestation, with all of this, with globalization, meaning people moving around from everywhere much more so than a few decades ago even, right?

Host: We weren't taking a boat expedition for weeks to get somewhere. Now, we could fly and be somewhere in a matter of hours.

Ana Bento, PhD: That's right. So, there's many factors that one makes us know that there will be other pandemics. In fact, we are in the midst of worrying about avian flu becoming potentially a pandemic, a project that I'm also involved with some colleagues here at Cornell and others from other countries. But really thinking about the types of data and the type of information we need to start getting that picture. It might not be enough for the next one because I do think that we are just simply not there yet. But the idea is to create these almost sentinel observatories of data in different parts of the world at different times in the year. And it cannot be something that is done for one year, and then we stop and then we pick it up elsewhere. So, it is also developing this idea of long-term research studies, like where I was trained, right? This SoWiSHI project that's been going on for years now. So really, kind of creating these infrastructures of studies that are kind of sentinels observatories across the world in different areas, thinking about to really quantify and identify these conditions that might allow for a particular pathogen novel or kind of not necessarily novel, but kind of stuck in one region, but all of a sudden some conditions allow it to spread, right? People always think about just novel pathogens, but it's not just the novel pathogens that can create problems. Really thinking about how can we build these data streams and how we connect these data streams to start telling us a story of risk, a story of conditions, and how one thing that is not a problem might become a problem very quickly.

Host: And I think-- and I'm sighing because I know that for some listening and others that they may know, it's hard to hear about some research and say, "Why would we do research on a virus that doesn't even impact us?" And I've asked this question before, and it's important to understand that financially we do need to support these types of surveillance and these of studies because prevention is much more ideal than undergoing or living through, I hope, a pandemic, right? We lost millions to COVID like this is-- so, I want to make sure, especially right now when finances towards scientific communities are in a tough place. Again, not a political argument, I'm just telling people how it is. And we need to understand the impact, right? And so what I want people listening to understand is maybe yellow fever sounds like something more novel to you, and we could talk about it and we could talk about how interesting it is. But we certainly don't want it to suddenly be everywhere in the Americas and beyond. We don't want avian flu to be in the Americas, everywhere and beyond.

So, I want everybody to just be really thoughtful about how you think about these things because they really can impact everyone. I hope they don't. Actually, that's why the surveillance is great. We hope it doesn't.

And so, okay, we've talked about a lot of heavy things. I want to ask you just a couple more questions because I've just been so just taken by this conversation. Thank you so much for spending your time with us. You have this really awesome section of your website. I told you all, I stalk websites and there's a page called Pathogens are Cool, which, yes, I agree. It also states like other values. So, why is this on your lab website?

Ana Bento, PhD: Yeah. like everything in life, you need a safe space to thrive. So, be it school, be it home, be it society in general. So, it's very important for me that everybody in my lab or prospective students or postdoctoral researchers know that I take diversity, I take safety, very seriously. Science is done-- as we've been discussing-- best done in diverse environments, but that doesn't only reflect different study fields, but actually different people coming from different places, experiencing different things in life, even before, way before they come to my lab. So for me, it's very important for perspective and current people in my lab to understand that that is how I see science, right? It's a hodgepodge of experiences and of points of view. And science is a lot more fun if we are very different, and that is really it, the idea of safety because we can only thrive in safe environments, but also to embrace that diversity that is not just field-based, but actually coming from different parts of the world.

Host: Yep. When we are safe and we can collaborate with others and feel free to express our opinions, it can have such incredible impacts in science and in our research. And again, I talk about this all the time, one of Cornell's mottos, right? Or the motto essentially is do the greatest good. And when we're trying to do good for the earth, we can also do good for the people that are helping us do this research and helping to make the earth better. And so, I very much appreciate that.

And if you're listening and you're like, "Why does anybody need safety? It's just a lab." I'm throwing my hands up because I'm from Queens, so if you're not watching, my hands are flying. We all need to be in a safe space when we study. We thrive when we are safe. And then this is where we make breakthroughs. This is where we pursue. Like, when we can be our most authentic selves, we can do our best version of science, right? Our best version of math. So, I so appreciate you saying that.

Okay. So, my final question for you, Ana, here, our expert.

Ana Bento, PhD: We're at the final question.

Host: I know. Well, I can't keep you here forever. You're studying all these diseases every day. There's no way she can make sourdough, people. There's no way. She's too busy.

Ana Bento, PhD: But I eat it.

Host: And I appreciate that. Okay. I am creating my zombie apocalypse team, which apparently I should have been taking more seriously as a question, because after talking to you, I really feel like I really need to get my stuff together. So, why does someone like me need you? On my zombie apocalypse team? What if you don't have access to a computer? I need to know what do you bring to the zombie apocalypse team? She didn't expect to get this question, folks. I'm just throwing this at her. I could've asked her hobbies. I also want to know.

Ana Bento, PhD: So to relate to my hobbies, I'm a fencer, so I'm very good with the sword. I could kill zombies, I coud kill zombies.

Host: What? I didn't have that in my notes. Okay. That's solid. That's solid. So, there you go.

Ana Bento, PhD: You could have me just for my hobbies alone. You can include me in your team.

Host: She came up strong with that one actually.

Ana Bento, PhD: Right? Even without a computer, I am trained to look at patterns, right? So, I can pick out patterns very quickly in changes in space and time. So, I can very quickly tell you something is changing or not changing. So, we can start kind of coming up with solutions for what's coming next. But in general, I think you would want me mostly for my sword-wielding skills in the zombie apocalypse. I don't think it's going to be because of my computer or mathematical skills. I think it's going to be I run fast and I'm very good with the swords. So, there you go.

Host: Hey, that's perfect. She's great with a weapon. She runs and, in her off time, she also does this amazing science. Dr. Ana Bento, thank you for humoring me with that last question. And thank you so much for being here and sharing. I know we've just touched the tip of the iceberg that is all that you do, but I really appreciate you sharing it with me and my listeners. It's been lovely to talk to you. Thank you everyone for listening. We hope you've enjoyed this episode of the Cornell Veterinary Podcast, and we hope you join us for our next episode. Take care, everyone.

Ana Bento, PhD: Thank you so much. And remember, pathogens are cool.

Host: She is right. Pathogens are cool. You heard it here. Bye.