COVID has exposed and possibly amplified the polarization of society. What can we learn from taking a multiscale approach to crisis response? There are latencies in economies of scale, inequality of access and supply chain problems. The virus evolves faster than peer review. Science is politicized. But thinking across scales offers answers, insights, better questions…
Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I’m your host, Michael Garfield, and every other week we’ll bring you with us for far-ranging conversations with our worldwide network of rigorous researchers developing new frameworks to explain the deepest mysteries of the universe.
This week on Complexity, we conclude our conversation (recorded on December 9th last year) with SFI External Professors Kathy Powers, Associate Professor of Political Science at the University of New Mexico, and Melanie Moses, Director of the Moses Biological Computation Lab at the University of New Mexico.
If you value our research and communication efforts, please subscribe to Complexity Podcast wherever you prefer to listen, rate and review us at Apple Podcasts, and/or consider making a donation at santafe.edu/give. Please also be aware of our new SFI Press book, The Complex Alternative, which gathers over 60 complex systems research points of view on COVID-19 (including those from this show). Learn more at SFIPress.org. Thank you for listening!
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Podcast theme music by Mitch Mignano.
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Related Reading & Listening:
“Spatially distributed infection increases viral load in a computational model of SARS-CoV-2 lung infection”
by Melanie E. Moses et al. incl. Stephanie Forrest
“Sunsetting As An Adaptive Strategy”
by Roberta Romano and Simon A. Levin
“The Virus That Infected The World”
by David Krakauer & Dan Rockmore
A Model For A Just COVID-19 Vaccination Program
Legacies of Harm, Social Mistrust & Political Blame Impede A Robust Societal Response to The Evolving COVID-19 Pandemic
How To Fix The Vaccine Rollout
Models That Protect The Vulnerable
Complexities in Repair for Harm (Kathy’s SFI Seminar)
"The inevitable shift towards science as crisis response is a call to arms for complexity science. How well we will be able to meet these challenges will determine the future path of humanity."
- Miguel Fuentes
Jessica Flack, James C. Scott, Sam Bowles, Wendy Carlin, Joseph Henrich, Luis Bettencourt, Matthew Jackson, David Kinney
Transcript provided by podscribe.ai with human edits by Aaron Leventman.
Melanie Moses (0s): I think that the misidentification of people as billiard balls, when in fact there are other people with cues who are pushing them around and there are springs connecting the balls to each other and to the walls. There's a lot of higher-level factors that in fact, there are these feedbacks between the individual choices and these upper-level structures, but it to just pinpoint individual choices without the context of the higher-level feedbacks, I think is completely missing the point. I think that is absolutely one of the important sort of lessons, not just for COVID, but for anything we want to understand in society,
Kathy Powers (35s): How do we organize for what we know and how do we create nimble organizational structures for what we can’t imagine. As these variants happen, as viruses mutate, there are organizational aspects and we're already behind on and we don't even know it. So what is the best that we could do is to how do we have a nimble structure that is dynamic and changing and can accommodate and adapt as necessary? And what does that even look like among the models of organization that we have, and is this where we need organizational innovation in ways we've never considered for the realities that are coming in?
Michael Garfield (1m 40s): Coefficient has exposed and possibly amplified the polarization of society. What can we learn from taking a multi-skill approach to crisis response? There are latencies in the economies of scale and equality of access and supply chain problems. The virus evolves faster than peer review. Science is politicized, but thinking across scales offers answers, insights, better questions.
Welcome to Complexity, the official podcast of the Santa Fe Institute. I'm your host, Michael Garfield. And every week we'll bring you with us for far ranging conversations with our worldwide network or rigorous researchers, developing new frameworks to explain the deepest mysteries of the universe. This week on Complexity we conclude our conversation recorded on December 9th, last year with SFI External Professors, Kathy Powers, Associate Professor of political science and Melanie Moses director of the Moses Biological Computation Lab at the
University of New Mexico.
If you value our research and communication efforts, please subscribe to Complexity podcast wherever you prefer to listen, email@example.com give. Please also be aware of our new SFI press book, The Complex Alternative, which gathers over 60 complex systems research points of view on COVID-19, including those from this show. Learnmore@sfipress.org.
Thank you for listening,
Kathy Powers (3m 32s): Complexity, breeds complexity. And we're talking about multiple levels from the science of the virus itself and how it moves is spreads and the way that it makes us interconnected to each other that we have to allow for. And how do we fight this? It can't just be you're taking a vaccine for yourself, but also for other people. Well, how do you get people in a society that's based on an individual sense of rights to recognize their collective responsibility in order to fight a virus and countries doing the same thing?
So for instance, former President Trump said in his last speech in the United Nations General Assembly, it is a world are diverse. We should all just protect ourselves. But how does that work with a global pandemic that requires that we understand our interconnectedness among countries, that we may have to give up some sovereignty or authority to an international organization to help facilitate cooperation among states to fight it. Or that’s a whole other discussion, and then getting down to the individual choices that people are willing to make for each other, not just for themselves, that's tearing apart the fabric of society?
And Melanie and I were talking about this. So the fundamental unit of societies is the family, but when you have families torn apart on these questions, what does that mean for how society reorients itself? So for instance, the pods that are starting to be formed of like-minded people who say my family no longer shares my perspective on this. So I'm going to form communities with like-minded people. And what does that mean for the reordering of the fundamental structures of society upon which are structures of power, knowledge science are all based?
I'll stop because I can keep going.
Michael Garfield (5m 29s): You're awesome. And you led me into one of my favorite questions of all time, which has to do with the latencies inherent in the coordination of all of these different agencies at all of these different levels, both individual and institutional and whether or not those latencies are fit to task for the response to a problem like this problem. You referenced the conversation that was had this morning, that involved Jessica Flack. Her work on collective computation helped me wrap my head around what I've started to think of as an institutional astigmatism, which is like the inability of organizations, we were talking about earlier, the blind spots that happen at the aggregate level and then all of the depth and nuance and dimensionality that ends up falling through the cracks when you are in the words of James Scott, seeing like a state part of this question is what kind of transformation can lead to a reduction in these latencies that can allow an expansion of vision and scope at the level of our institutions at the level of our states and of our markets.
Just to tie into a piece that Wendy Carlin and Sam Bowles wrote during the early stages of the pandemic for Vox EU, they wrote this piece on the return of the civil society and how economies of scale have hollowed out precisely what you're talking about.
The mesocosms, the neighborhood, the clan. Historically, there's Joe Henrich's book about the weird and how so much of the identity of Western society he argues and this is a non SFI perspective, but it's an interesting perspective is contingent on marital taboos that were put into place by the Pope that forced people to marry outside of their village, outside of their family and contributed significantly to this modern culture of individualism in the west and the horrific isolation that so many people are experiencing under these conditions.
I'm going to kind of fork this so that we can make room for Melanie to talk about her work on spatial modeling and the lungs too, because one of the other things that comes up for me in thinking about this is, like for instance, when we had Luis Bettencourt on the show and he was talking about repairing slums and favelas by analyzing their network structure and identifying where you need to sort of trench in roads and other infrastructure into these dense, almost like a tumor mass inside of a city.
And, our first piece, you talk about how disease spread is an inherently multi-scale spatial process, and that COVID-19 will grow where the most vulnerable are concentrated in refugee camps, favelas and war-ravaged cities. I think I just asked you two totally different questions, but this issue, which is related to so many other issues, such as the conflict between the pace of regulation and the pace of technological innovation, for instance, and the apparent inability of state powers to stay on top of the innovation in that space, which is directly adjacent to the two of you and your work on justice.
Again, this is like an enormous sort of ball of sub-component questions, but I'd love to hear you pick on that. And Melanie, this is your opportunity to discuss this paper that was just accepted for publication.Do you want to continue on that thread? And then I'll probably more mathematical take on it?
Kathy Powers (9m 6s): No problem at all. And the hard part is at what point in the process of the pandemic are we talking about because the questions are different. So for example, we're living in a time now where there are people who feel like, and they use the language post pandemic. And so they feel like it's behind us. And so people's behaviors have changed. You have those that are vaccine resistant for good reasons, for historical reasons, but then you have people at the other end of the spectrum who say, why be vaccinated?
So I don't need to wear a mask. I don't believe that I'm now susceptible to the variants that are now emerging. And so our behaviors are changing. People are traveling. So the questions we're dealing with now are totally different from a year ago and the evolution of this pandemic,. I think we've got to break it down into stages almost of the pandemic, as a first emerges, as it takes hold, as we have the first variant. Once the vaccine emerges, that changes everything and people's perspectives.
So that's first is I think that our questions are different at different stages of the pandemic. It is very important that we sort of think about this because as we know with climate change, the possibility of this happening, not only is it not just possible, but with increasing regularity. I used to work in the insurance industry. I don't know if Melanie knows this in executive protection for Chubb insurance group. So it's like insurance for wealthy people and corporations. And it was at the time that there's a trout in the Southern U.S. effected farms and rain insurance.
Well, the insurance industry has completely changed and it's two processes going parallel and intersecting. How has climate change impacted the insurance industry and how have pandemics and then the interconnectedness between the two at each stage that we're talking about. Also want to say how these issues are dealt with on the international level, depends on what you think the problem is. So for many there's the criticism of countries and pharmaceutical companies that if we waived these patent rights that pharmaceutical companies have to limit, or to make sure that no one else produces the vaccine that they've created, that that's the problem with vaccine equity and distribution and access. What the pharmaceutical companies argues that's not the problem. It's the global supply chain problem. It's the lack of companies that have manufacturing capabilities and that's the problem. So stop putting pressure on them to waive their patent rights and work on the global supply chain. And I would add another factor and I’ll stop here. We're not paying attention to the number of people who died on the planet. If anything, the bubonic plague in the 19th century taught us from an economist perspective when people died there weren't people to do jobs across the border.
So wage, labor prices went up. So when we start talking about people's choice, not to work, it drives me nuts. Maybe we don't have enough people because so many people, either they have long caught Covid, which is now a disability and they can't work, or many people die. And why aren't we talking about that and its impact on the labor market in the United States and globally, as much as we're talking about people's choices not to work at all, which if you look at the growing homeless population across the countries, like 30% a year in San Francisco who is choosing not to work and is that like a phenomena of higher socioeconomic status, but for the poorest people, I'm not sure that that's what's happening, especially if they were on the front lines and they were at risk.
Maybe they're still sick. Maybe they died or maybe they're homeless. Maybe there are these other dynamics going on, but we're focused on people's choice not to work, which is for me like a mask for a whole lot of things going on. I'm going to stop there. I get too preachy sometimes.
Michael Garfield (13m 18s): If I may just briefly interject it is I think that there is what you're speaking to as part of this much bigger epistemic shift, again, that we see in complex systems thinking from regarding the individual as this sort of billiard ball of self-determination to this more sort of networked algorithmic kind of construction of individuality. We talked about with Mirta Galesic and the way that people's opinions are based on local network bias.
And so, yeah, of course, like I going to issue an armchair hypothesis here, that part of the issue with the overemphasis of individual choice in this matter is that the people assuming this are the same people that are blaming people for poverty, that are regarding financial success as a matter of merit rather than one location in a network, as we discussed with Matthew Jackson back in episode 12.
Melanie Moses (14m 14s): So I think that the misidentification of people as billiard balls, when in fact there are other people with cues pushing them around and there are springs connecting the balls to each other and to the walls. There's a lot of higher-level factors that in fact there are these feedbacks between the individual choices and these upper-level structures, but it to just pinpoint individual choices without the context of a higher-level feedbacks, I think is completely missing the point. I think that was absolutely one of the important sort of lessons, not just for COVID, but for anything we want to understand in society.
I wanted to say a couple of things about the vaccine scarcity problem in the face of exponential growth. And this also relates to the latency problems. So first, just to put this in context of this moment, which will be very different by the time this airs. So right in this moment, I think it was yesterday, the torrents of papers, every few hours there's a new paper out talking about the vaccine effectiveness at largely preventing transmission. What's the antibody response to the Omicron experience. And I do think it has been about every three hours when new papers come out in the last 24 hours.
And one of the messages from this is that we all need boosters, that if we want to prevent transmission, if you want your antibodies to block this new virus, the new virus that your antibodies are not as effective, so you need more of them. And so to have any shot at blocking transmission in really substantial ways, then we need three shots. And in the same, I think press release that Pfizer talked about this they said, it's okay, three shots. We'll do it. We'll be able to protect you. And we're going to make 4 billion shots next year. Well, that's great. There's 8 billion people. And if we need three shots each like do the math, there's an ongoing scarcity problem.
There was a moment of in the beginning of the pandemic, when there's scarcity in the U S where these questions about who should get vaccinated first, then it was in the face of the alpha variants . Those were extraordinarily difficult questions. Do you vaccinate an elderly person who has very likely to get sick or maybe a middle aged person with co-morbidities who slightly less likely to get sick, but has 30 years of life left to live in three kids at home. And those kinds of vaccine prioritization questions are now playing out internationally. And they're terrible, terrible question to ask.
We should do everything. We cannot ask those questions. And the way to avoid asking those questions is to remove the scarcity in the first place. And so clearly the model that we have, isn't capable of producing vaccines at the speed that we need them. And so really we've got to look at, so as Kathy talked about, is it the IP? Is it the supply chain? Is it the trust of people in the system itself that's limiting uptake? Yes. It's all of those things that we have to go full force. We've had these vaccines for a year. And so to still have the same excuses of, oh no, it's not my problem.
It's some other part of the system. That's an old story. We have a lot of levers to address the latency issue. I think we need to address all of them and stop using sort of each problem as an excuse for not fixing one of them. One thing that I think is really crucial to talk about is the problem of latency when facing something that's growing exponentially. So this virus is growing exponentially really quickly in ways that I think don't appreciate. So one of the shifts with Delta is that people talk about the rate at which the virus spreads for them in idealized non-existent situation as being approximately two and a half to three times faster than your original constraint.
That sounds kind of bad. That sounds bad. But putting it actually like into an equation and looking how fast that is, the original Mohan strain, this is a little faster than that, but if you have something that's transmitting every three days, which is probably about where we are now, I'm on Makonnen, Delta transmit every three days. If you double every three days, then in a month, a case turns into a thousand cases, two to the 10. And in two months, it turns into a million cases to the 20. If you just increase that by 50% now, your spread is you're tripling every three days, then you're at 59,000 people and month one and half the planet in month, two and three days later, everyone is infected.
You have growth rates at that rate that really maintain at the rate that Omicron is currently spreading. I think there's lots of reasons to think that it'll slow down, but at current actual exponential growth rates of Omicron, two months and it swept through the planet already. So a vaccine production while that says, oh, we're going to have an Omicron variant specific vaccine in March is largely useless. So we really got to figure out how do we slow down the spread using other methods? If we think an Omicron conspecific vaccine is necessary, or if we think the current vaccines that we have, we need to get, you know, three shots in people's arms across the planet.
Like we're just not facing sort of the scale of the problem. And what we've seen so far is that, that skill on the part of the virus it's getting faster, it's replicating faster, it's entering cells better, variants are coming out with extraordinary evolutionary change, far faster than you expected. And our lack of ability to adapt quickly, which changing landscape that along with our misinformation problem, I think those are sort of our two key societal issues.
Michael Garfield (19m 13s): So before we guarantee that we get to your lung modeling stuff, I really want to press on this particular issue with you both because something that I really enjoyed reading Miguel Fuentes reflection for this series, in which he said that the inevitable shift towards science as crisis response as a call to arms for complexity science, how well we will be able to meet these challenges will determine the future path of humanity. And he was just talking about how the process of science itself has changed.
Our expectations for science itself has changed the way that COVID is moving faster than peer review, the way that we had that awesome piece that was led by Joe Beck Coleman and had a number of SFI coauthors on understanding social media and digital communications technologies broadly, and the research into those as a crisis discipline, that is part of the compounding issue around all of this stuff. And again, this is tied to a really fundamental thing within complex systems thinking, which is about the inverse relationship between the model complexity and the speed at which you get an answer out of this thing.
And obviously we spent most of this conversation hammering on the inadequate complexity of our models. But there is some threshold at which, again, we're just not using too long on this. And so we're in this weird spot where I feel like you, and so many other members of this scientific community that is committed to rigor, are being forced into a kind of Stanford Design School fail fast kind of iterative thinking.
And just to step back into the meta a little bit, I'd love to hear your thoughts on the challenges to science as a social endeavor. When we talk about institutional transformation, it seems like one of the most obvious places where that is going to have to take root is in the practice of science itself. And I'd love to hear your thoughts on that.
Melanie Moses (21m 15s): I think it is worth taking a moment to actually celebrate many of the scientific tools that have been developed during this pandemic. Phenomenal. I mean, absolutely astounding that vaccines were produced in 10 months and began to get injected into people's arms. And they're far safer, far more effective than anybody had any right to expect going into this, understanding how the virus is spread and the idea of airborne transmission. The scientific understanding is great. The public understanding, maybe not as good, the ability to do rapid testing, all of these tools.
I think it's worth celebrating. And considering this as a real scientific accomplishment, that we were able to build these tools to help fight the disease. And along with that is the rapid communication. So right now I think it was two weeks ago, this Omicron variant was identified in South Africa. By some diligence scientists who noticed something that looked a little odd. And two weeks later, we know an incredible amount about this new variance. We also don't know an incredible amount about this new variant. And so we're, I think perpetually finding ourselves in the situation where science is uncovered knowledge and it's really rapid rate, but there's some pieces of understanding that we don't have yet.
For example, how severe is this disease going to be in naive people? We have no idea at this point. And there's communication all over the place screaming, oh, it's so mild. We should all run out and get it. And other people saying, look at these 50 mutations, it's going to be the worst thing in the world. And we just don't know. We have to wait and see. And yet we're facing this exponential with if we wait a couple months to get answers to the questions we're used to answering before we act, then it's too late. I think it's a really fascinating question. Like how we got ourselves to this point. If this were 50 years ago and we were facing the same pandemic, we'd have no idea what was going on.
We'd have these waves of infection happening. We'd have no idea that it was when a variant showed up and when it didn't. We wouldn't have had that ability now that we have that ability and we have scientific tools to use them. I do some the big challenges. How do we organize ourselves to use the information that we have rapidly to change course rapidly when we need to? So I'm going to say that science, as we used to conceive of it as building tools and understanding disease has done a great job science that actually protects society because there are the social and political structures to use it.
Well, it's a pretty big failure that we could have done so much better. And so I think that figuring out how we work under some understanding and a lot of uncertainty quickly is really a question.
Kathy Powers (23m 45s): So I would sort of extend what Melanie is saying. I agree it's an achievement. And we haven't had the space to step back and recognize vaccine development so quickly with some level of effectiveness. Also the international cooperation that was necessary among a host of actors for this to happen that was unprecedented. When countries are seen as protecting their sovereignty, making self-interested decisions that there's these debates about, are they using international organizations to pursue their own interests or to solve global problems that they are mutually affected by, but can't solve alone.
But in this case, we saw states, governments, pharmaceutical companies, scientific organizations, medical organizations, sharing information at an unprecedented rate where the consequences for scientific credit could be at stake recognizing that global health was at stake. The scientists that we don't know about who may be for went the opportunity for a major publication to share information in order to fight this virus, that sort of level of cooperation that was necessary, that we'll never know about, the interplay between science and government, that's going to be increasingly important.
You know, there are people who said, Dr. Fauci should be president, that we need a doctor who should be president next time. And so the politicization of our medical and scientific institutions, there was criticism of the CDC. As our presidential administrations change, the political pressure that a scientific organization faces. And how does that impact scientific development?
What gets funded and what doesn't get funded, scientific policy recommendations? For some people who are anti-vax they said, I can't trust the CDC anymore because it's become so politicized are the recommendations scientifically-based or are they politically based? And to Melanie's point about how do we organize, oh man, this is just one that keeps me up at night. And I'm thinking about how do we organize for what we know and how do we create nimble organizational structures for what we can imagine. As these variants happen, as viruses mutate, there are organizational aspects and we're already behind on, and we don't even know it.
So what is the best that we could do is to how do we have a nimble structure that is dynamic and changing and can accommodate and adapt as necessary? And what does that even look like among the models of organization that we have, and is this where we need organizational innovation in ways we've never considered for the realities that are coming.
Michael Garfield (26m 43s): Thank you, Melanie. That was a beautiful way to state this, Kathy. And I think that that is a little bit what I was getting at with the immune systems or models to this simultaneous speed in the short term, and also this sort of adaptive broad approach that it's nimble for the long-term. This came up recently with this travel ban on South Africa. This topic, we didn't talk about. In the abstract there are places where a travel ban is a necessary public health tool. And if used wisely to buy time, to slow the spread of a virus from one place to another, it could actually be helpful. It's part of an integrated system that actually uses that time extremely wisely and repairs, the harm done to the people who are banned, but that's not what we do. We use these sorts of things selectively. We put a ban on South Africa, not on a UK when there's a new variant emerging, but most importantly, it's a failure to see the long game because Omicron is not going to be the last variant.
We see somebody else in some countries is going to notice the next variant. And if what they see is if I speak up about this, my country is going to suffer tremendous economic harm. And who knows how long unnecessarily this restriction on our travel is going to last. We've already passed the point. I'm sure we're getting more cases in from the UK than we are from South Africa at this point because we have more flights? We would have more tools at our disposal if we could dispose of them, we don't need them anymore.
I think is absolutely characteristic of our problem. I was going to use that as a segue. Is that okay?
Kathy Powers (28m 34s): Although I did, I just want to, just to pack that into another kind of superficially unrelated paper. There's the piece that just came out in that special issue of P and S on the evolutionary metaphor as applied to financial markets and sun-setting as an adaptive strategy. And again, like this question of like broadly speaking, when is it time to let go?
Melanie Moses (28m 57s): So I did want to take this moment to talk about a paper that we wrote that's modeling a different spatial scale. We have a paper that's coming out in plus computational biology on a model we created called SIM code, which is a spatial immune model of Corona virus. And it's specifically of spread in the lungs. So I'll take no more than a minute to sort of give the overview of that. So essentially we built a model of the virus spreading in the lungs for two main reasons. One is lung infection that makes people severely ill. The virus can infect your naval cavity, but also, you know, when it gets into your lungs, that's the first site of severe disease.
It likely goes on to other organs for longer term severe disease. But the lung has a really sort of critical infection site and we don't have much visibility into it. We take nasal swabs, nobody's swabbing their lungs. We don't know what the virus prevalence is in your lungs and measuring that is difficult and uncomfortable. And so we don't have a lot of measures of how the virus is running along. So we build computer models of it. The other reason the lung is most important is it's where the space is. It's where you have lots of cells that can get infected. So we built a model of the fractal branching airway. It's really exciting for me to complete my first work at SFI, as in understanding the fractal structure of circulatory systems and the lungs with some more structure, it looks sort of like you can imagine your lung is a piece of broccoli, which you pulled at the stock and branches lots of times.
And your air is breathed in as a little florets at the end only, and you have 26 generations of this and it makes an enormous surface area so that if you took your lung surface area and you spread it out flat, it would be about half the size of a tennis court. That's 15 square meters. It's a very large, very large surface that can be infected. And SARS, cov two is a virus that is able to infect probably from your first inhaled aerosolized virus infected deep in your lungs. So it's different from flu, which tends to infect your upper respiratory system.
And so it's three orders, a thousand times more space there. It can get infected than your nasal cavity. And so we wanted to model the virus dynamics in that space. The main message that is unique from this modeling exercise that consider spatial dynamics, is that because your lung is so large, again, we can't have this well-mixed assumption and infected. So on your let's say the left lower lobe of your lung is not going to infect a cell on the upper right lobe of your lung. It's spread slowly over spatially.
And that space actually constrains the spread. It's much slower than it would be if you had sort of a wellness model. But what we were able to suggest in the model is that it matters how much virus you inhale, because if you would hail a large amount of virus, let's say you're in a crowded room with, poor ventilation, you breathe in a lot of virus. It goes through this fractal branch Instructure, and it can infect different spots in your lungs. And each of them can replicate sort of independently without shading other pieces of it. So essentially what that means is the more virus you inhale, the larger your peak viral load a few days later, and that means more tissue damage, more need for immune response that can further damage tissue and really importantly, more probability of infecting someone else because that viral load that you have yourself is related to how likely you are to transmit the virus.
So we wanted to model this process and I think that's an important insight because it does relate to what kinds of controls we want. It highlights the idea that we really want to prevent inhaling large amounts of aerosolized virus that can get these in along and spreads different locations. So, very good masks and 95 and kn95 masks are really good. Even if they don't keep you from getting infected, that lowering the amount of virus in your lungs, cleaning the air. So not wiping the surfaces. You're not going to get a virus in your lungs from a desk.
You're going to get it floating in the air. And so this points to reasons, these kinds of controls, and a lot of public health experts have been advocating for that. We've not done perhaps again, going back to these institutional barriers, we do have mass mandates, at least in New Mexico and in different places. And you can sort of put that kind of control on individuals. Cleaning the air. Is it something that requires building managers to do. You have to have an institutional response that it's the responsibility of the person running the restaurant, owning the building, probably the responsibility for government to fund people to do this kind of work, but that is a barrier.
So that's sort of another one of these links like down at the cellular level, what happens to the infection in your lungs? Well, that depends on how well somebody cleaned the air in the building that you're residing in. So we think that's an important insight that it matters how many different places you get an infection. And then what we've done in the model is it's an agent-based model. And we model both the virus and the immune response focused on the, what are called turchin cells. So these are the immune response, the components that kill infected cells and are probably the most important part of the immune system for preventing severe disease.
And what we're looking at now, and know you can model and sort of say, how many T cells do you need? And when do you need them? If you're not infected before it takes about seven days before your T cells can undergo their own exponential growth to have a big enough army to go fight this invading pathogen, if you're vaccinated or you've been exposed before, they probably arrive in about three days. And so all of these different scales, fighting COVID is winning a race. And in this case, being vaccinated basically gives you a head start. And so what we're looking at now is how the dynamics of that head start might play out with different effectiveness of those T cells in the face of different variants and different amounts of inhaled virus that might also change the variants.
Different variants may be able to be aerosolized differently. So we're essentially trying to use this computer model to get some early hypotheses for conditions that have all sorts of variables going into this equation, which ones of them are likely to matter to sort of suggest, for example, like which population should you prioritize giving a third booster too, because they're sort of at this tipping point where if they have just a little better T-cell response, they can be protected from severe diseases. Whereas other people made you're very far from that tipping point and won't be protected from severe disease, but more likely it's very healthy people were protected. Anyway, don't use the word restrict probably in the face of Omicron, cognitive, everybody needs a third person, but I think that another place that we didn't talk about where latency in decision making is really important and computational models can help isn't treatment. So we know that most of the antivirals and the monoclonal antibodies that can help people who are at risk of getting sick, severely ill, have to be given very quickly before you really know that they're severely ill. And so it's very helpful to identify which people are most likely to become ill.
And if we have a variant that is reinfecting people, so if really large numbers of people who are going to have mild disease it's more important and more difficult to identify which them are the ones that we want to prioritize our limited, monoclonal antibodies for enterprise roles for. And so what we're trying to do is provide, I don't think a computational model will provide answers, but hopefully it provides a constraint set of hypothesis that focuses where you can do biological laboratory studies to be able to kind of assist in those decisions. So ultimately I hope that we kind of link this kind of modeling we do within the lungs to the kind of institutional changes and the institutional responses from the medical system all the way up through political systems to make our societal response better.
So that's a dream.
Michael Garfield (36m 12s): I don't know that I'll leave this in because this is kind of a naughty question. It's a naive question. Hearing you talk about this stuff, hearing you talk about it, using the computational models to identify which people are most likely to become ill. The question of how response at different layers account for different latencies. And then going back to everything that we've just discussed on the balance between our tensions between individual response and institutional response, the way that it seems that people's narratives around this have diverged precisely how they decide to emphasize individual agency versus institutional agency.
People are saying, it's not my responsibility to ensure other people are healthy, this kind of thing. It seems like it also aligns with the lens on the coordination problems around climate change and, things like BP gaslighting its customers with carbon calculators and like the amazing response that they got from the Twitter community. They were just like eaten alive for that. And as a roguish individual, I appreciated that. But anyway, so the question is if due to exponential spread, it seems kind of unthinkable that we're going to be able to manufacture vaccines quickly enough.
And we have all these questions about prioritization. Why aren't we prioritizing vaccines for the people who want them, like doesn't that cut through problems around communication and trying to win back the trust of all of these people who don't want to be vaccinated in the first place. I don't know what your thoughts are on that. Or even if that's like something we should include in the final cut. But I am curious,
Melanie Moses (37m 53s): I'll give you my initial thought. When vaccines were scarce in the U.S. we prioritized by, some measure of risk older people, first, for example, but if someone didn't want to, wants to get the vaccine, right, we moved on to the next group. I think the big problem with that form of prioritization is not recognizing that it is in fact, a privilege to want one. And then it is the people who reasonably expect the system to protect them who are going to want the system to protect them. And they, in many cases will be the least in need of protection.
There are practical advantages to vaccinating the person who can show up at the vaccine site at 7:30 on Monday morning. And this is the person who's wheelchair bound and just can't leave their house. There's practical reasons to vaccinate when you can first, but if this is another one of those short game versus long game things, so this is a way to address short-term latency and exacerbate from long-term problem for privileged, continuing to get more access to things that protect them. And I don't know the answer
Michael Garfield (38m 54s): You put that in the reflection that that trust is itself a privilege. Thank you. That's a good point to hammer home.
Kathy Powers (39m 3s): So I would say first there's the practical matter of how many people must be vaccinated to have herd immunity.
And so we're saying, if we only vaccinate the people who wanted, how many people are we talking about as a percentage of the population and how does that affect the ability to deal with the interconnectedness among us? That is part of how this virus works. Also There are institutional responses that have already happened to deal with the question of people who want to get vaccinated and people who don't. And these institutional responses that have been used, these vaccine mandates that we've had.
So, there are the travel bands, but there's also, you are automatically withdrawn from your classes if you don't demonstrate that you vaccinated. You may have a fellowship to come into the country, but you can't come. If you are not vaccinated, there are consequence. I mean, I've even seen on the east coast where there have been art festivals, and if you're not vaccinated, you can't participate. So we've already seen institutional responses to deal with how do you compel people who choose not to be vaccinated?
And their interpretation of this is my human rights are being violated. I'm being excluded from society. The excesses of the government are impacting my human rights. And then on the other side, people say, but because of the interconnectedness and how this virus works, you're impacting my human rights to live, my human right, to not be exposed to illness. So these camps are forming as a function of this and the institutional responses are raising more human rights questions.
For example, like not only do we have the vaccine access equity and distribution problem internationally, but also it's going to determine who can cross borders and who can't. So we're talking about travel bans and what vaccines do countries have access to? There are those that are accepted by the World Health Organization, but there are vaccines like the United States doesn't accept Sputnik, but what if you're from a Latin American country that bought the Sputnik vaccine? So you may have a fellowship to go to the United States, but you can't take it because you had Sputnik.
And then what are the health consequences of having to be vaccinated again when you get to a new country. There's also the question of, do you have to be vaccinated before you cross the border? So if you're in a place like Russia, where only Sputnik is offered, but you have opportunities to go to other countries and we get to the point that you have to be vaccinated before you come in, how is that going to change travel flows? We will see an emerging shadow economy or black market in vaccines as they determine when and where you can go in the world.
And if you have to have access before you get there, but what if you can't get access in your own country? So we're talking about illegal flows that already exist. We've seen them as vaccine cards, but we're going to see it with counterfeit vaccines and also if these rules about who can cross borders and who can't are guided by these questions.
Melanie Moses (42m 35s): It's so hard to have. the way the next layer of the onion.
Michael Garfield (42m 51s): It is complexity all the way down. I feel that it's funny because I find that often when I'm talking about this kind of rat king of interrelated issues, it is really demoralizing to people to realize that there is no simple answer. And yet I find in that to draw on the talk that Stuart Firestein recently gave at SFI about uncertainty and optimism. I think that there is something really beautiful lying in potential on the opposite side of this, where we are encouraged to adapt to the profound uncertainty of our century into a position that I think reflects the move from science as most people are taught in school to the way that complexity science is practiced, which is an appreciation for the uncertainty or recognition that our claims have to be couched in confidence intervals. David Kenny wrote about this in terms of the collision between scientific rigor and policy making and the way that policy makers want clear, simple answers. And this is just a challenge, I think, to the paradigm of modern society and acceptance of the fundamental uncertainties in our world.
And we'll get out of this actually more humble and more honest with ourselves as a species, you know, assuming we survive.
Melanie Moses (44m 16s): I think that is absolutely right. This is not an extinction risk for humanity. We could've done better. I think there's 7 billion, almost the number of people on earth, not equally distributed, but there's 7.8 billion vaccines have been injected into arms. And the hard part of figuring out how to cooperate with each other and work together, I think we're going to learn a lot. I think there's a real reason to hope that will come out of this with the ability to have the kind of subtle nuance, maybe even constantly changing conversation in the face of the constantly changing threat that we're going to need if we're going to take on challenges like climate change. And so hopefully this is us putting on the training wheels for how do we deal with a really complex adaptive global threats. And maybe we will actually build up some institutions that are more up for the challenge than we've seen
Michael Garfield (45m 4s): That feels like a better place to end. Well, thank you both so much for taking an absurdly long time with me to explore this. I think we're going to have to break this up into two episodes, but that's not a problem that just gives me more time to share your work with everybody. So again, thank you both so much.
Melanie Moses (45m 25s): Thanks for all those balls of yarn. Really appreciated this question and the chance to talk with Cathy about people tools. Again, it's very mind opening to think that these different scales good. Thanks Michael.
Michael Garfield (45m 38s): So much. Bye bye. Bye bye. Thank you for listening. Complexity is produced by the Santa Fe Institute, a nonprofit hub for complex systems science located in the high desert of New Mexico. For more information, including transcripts research links and educational resources, or to support our science and communication efforts. Visit Santafe.edu/podcast