Distinguished Colloquium Speaker Series

Description of the video:

Description of the video:

All right. Well, welcome to our colloquium. We are so happy to have Dr. Brian Mustanski here. I have an actual thing that I'm reading for you, even though I would normally introduce you a different way, but here we go. It's formal. Dr. Brian Mustanski earned his Ph.D. in psychology from Indiana University in 2004. He was an engaged student and took seriously the opportunity to grow both his research and clinical skills. And I mean that, right? Like you were, you from the get-go. We're here to learn and to grow. And I mentioned that for all of those who are here early in their career. And you're thinking about how do I have a career that looks like this one day? Well, after Brian's time at IU, he went to UIC, where in 2008, he started IMPACT, the LGBT Health and Development Program, which is a home for research that seeks to improve the health of the LGBT community and increase understanding of the development of sexual orientation and gender identity. He brought this program to Northwestern, where it became a university-level institute known as the Institute for Sexual and Gender Minority Health and Wellbeing. And in 2025, with a nod to their roots, it was renamed as the Impact Institute. Dr. Mustansky is also the founding co -director of the NIH -funded Third Coast Center for AIDS Research in Chicago. And as the son of an educator, Brian also noted important gaps in the sexuality education of young LGBTQ youth. To address those gaps, he created innovative digital media education projects like Queer Sex Ed for LGBTQ teens and Keep It Up developed specifically for gay and bisexual men. And for those of you who aren't familiar, sex education in the United States, when you ask young people what they learn, usually around only six to eight percent of them recall having any information about how like two women have sex together or how two men have sex together. It's just really pretty non -existent. So to create that is critical. Dr. Mustansky has led the longest longitudinal cohort study of LGBT youth and an innovative adolescent extension of the National HIV Behavioral Surveillance Study called Shy Guys, which was funded by the CDC and engaged young men ages 13 to 18. He drew from these and other cohort studies to create RADAR, a dynamic dyadic network cohort study of over 1,000 adolescent and young adult men who have sex with men that examines HIV and substance use through a multi -level perspective. Brian served as the 46th president of the International Academy of Sex Research and is now the associate vice president for social and behavioral research at Northwestern University. He's been a principal investigator of over $70 million in federal and foundation grants and has authored or co-authored more than 375 peer -reviewed scientific publications related to LGBTQ health, adolescent health, mental health, HIV prevention, substance use, and sexual health and behavior. In 2017, NBC News selected him from 1 ,600 nominees as one of 30 changemakers and innovators making a positive difference in the LGBT community, and they've got a great interview with him online. Dr. Mustanski's work has made it possible for thousands of young people to receive free HIV testing and for those who test positive to be supported in their care. His research participants have described being in his studies as sometimes the first time that they were provided with kind care, which speaks both to the kind of research team that he's built, as well as how far we still have to go to meet young people's needs. All of this is incredibly impressive. But as someone who's known Brian for more than 20 years, I can also share that in addition to being an exceptional researcher and educator, Brian is also a thoughtful, self-reflective, lovely, and fun human being, and a devoted friend and caring colleague to so many. Please join me in welcoming Dr. Brian Mustanski. I keep going for a while. Heaven, beautiful. Thank you, Debbie. I'm going to have to find an opportunity to pay it forward and introduce Debbie at some event in the future. Well, thanks for having me. It's a real pleasure to be back here with you. I'm going to try to share a little bit about kind of the arc of my career, share some findings from a couple studies. And then try to leave a fair bit of time for questions. I think we have at least 15 minutes built in for questions. But also, we're not a huge group. So if there's something, as I'm going through a slide, that you want to have a clarifying question, feel free to just raise your hand and we'll kind of address it as we go. All right. So just a little bit about my career path. I did my undergraduate degree at Northwestern University. And during that time, I was introduced in some undergraduate psychology classes to research on behavior genetics. When I was an undergrad, I wasn't sure if I wanted to go into genetics or possibly psychology. And there was a psychology class where they introduced work on behavior genetics. And I was like, oh, wow, this is the fusion of two things that I can't decide between. So why don't I just lean into that? and was very fortunate to get accepted to the Ph.D. program in psychology here at Indiana University because it combined many things. One, they had some great work on behavior genetics, including these very large studies of twins in Finland. And then also the Kinsey Institute was here. And so I had an opportunity to do work on sexuality and sexual health, learn a lot about providing sexual health services. I worked in a clinic there, providing care for folks experiencing sexual problems. And then also, it was a time when like a lot of behavioral scientists were starting to get engaged in HIV research. And there was some HIV research that was happening at the Kinsey Institute that I was fortunate to be able to get involved in. And so as I was finishing graduate school, I was sort of still doing work in behavior genetics, publishing papers using finished twin studies, but also getting involved in HIV research. And all the work I'd done on twins was really focused on adolescents and young adults and understanding the development of substance use and health behaviors using that approach. And then, so I wanted to continue work with young people. And so my residency was matched at the Institute for Juvenile Research in the Department of Psychiatry at the University of Illinois at Chicago. And there I had the opportunity to get mentored by some senior faculty who were engaged in HIV research, including Jerry Donenberg, who's now the director of the Office of AIDS Research at NIH, and started to do more work on HIV in young gay men, it felt like it was really combining my interest in sexual health with my experience with adolescents and adolescent health, and so started to get involved in some very early studies of HIV in young gay men. I went to a conference focused on HIV in young people and presented some of the work I was doing in young gay men, and I was shocked to be at a conference focused on young people, and I was maybe the only person focused on young gay men. The majority of the folks were focused on heterosexual young people and a lot with a big focus on heterosexual young women. And I actually gave a talk at the conference where I showed some of the CDC data that about 80 percent of HIV infections in young people in the United States are in young gay men. And people were very disturbed by that. They were like, why are you talking about this? This is not the face of AIDS in our country. Why are you focusing on young gay men? You can't study them. It's too hard. How are you going to find them? How are you going to get parental permission? no, we need to keep the dialogue focused on young women. Bush was president at the time. There was a big focus on HIV in young girls. And I was like, this is not going to work for me. This is like the biggest group of HIV infections. I'm a young gay, at that time was a younger gay man myself, not so much anymore. But, you know, I was like, this is, this is, if no one else is going to do this, or if not that many other people are going to do this, this is what I'm really going to focus my work on. And so that has really shaped my career for the next 20 years. And I've done epidemiological studies. I've done studies developing interventions, primarily using digital health approaches as a way to reach people that we might not be reaching through traditional approaches like sex education in schools or clinics or community organizations. As Debbie mentioned, when I brought my research program to Northwestern, it became eventually a university-wide institute called the Impact Institute now that's focused on supporting research on LGBT health. We're a very community -engaged, community -based institute. My largest study called RADAR, which is a cohort study of young gay men, is embedded in the community. We actually run it out of Center on Halstead, which is the LGBTQ community center in the city. So happy to talk about all of these things. And because I came to this work because I wanted to make a difference in addressing HIV in young gay men, I ultimately started getting involved in implementation research because it really wasn't enough to just publish our findings and say this intervention works. And really, we needed to understand how can we actually get services to people who need them, which is a different kind of question. So I'm going to do a little bit, just not knowing necessarily people's backgrounds. I thought I would give a few minutes on just like, what is implementation science? Why do we need it? Why did I really get drawn into this particular scientific sub-discipline in the last decade? And so I'll share a couple examples with you about what the point of implementation science is and some examples of how we've done it. So many of you may know, HIV is still a continuing issue in the United States. There was some evidence that maybe rates had been declining in our country, but actually there had been a little bit of an increase in diagnoses in 2022. Possibly, the CDC had estimated those might have been cases that had been delayed in diagnosis because of COVID and lack of access to testing. But actually, the 2023 data that just came out actually is putting the number even higher. And so it's possible that we're actually not showing declines in HIV cases in the United States. It's been, unfortunately, very stable for a long time. And it's stable despite us having highly effective interventions that prevent transmission, that prolong people's lives, that are highly effective in terms of testing. We also know that HIV cases are not randomly distributed amongst people. Men who have sex with men continue to represent about two -thirds of new HIV diagnoses in the United States, So over 25,000 each year in gay and bisexual men. And layered on top of that are some racial and developmental patterns. So the largest group of new cases in men who have sex with men each year are in 25- to 34-year-olds. So young adults. But after, and for about a decade, we saw increases in cases in 13- to 24-year-olds, which might now actually start to be going down. But that's still the second largest number of group in terms of new cases in the United States. So we see these developmental patterns that we really must attend to in terms of new cases. And then there's also racial and ethnic disparities. In 2022 was the first time that actually there were more Latino men who have sex with men diagnosed with HIV than black men who have sex with men. We are seeing perhaps some trends towards declines in HIV cases in black MSM. But we're seeing some big increases in Latino and Hispanic men who have sex with men. So there are racial disparities, developmental disparities or sexual orientation disparities that are sort of all overlapping. Now, I mentioned before, you know, we have we're at this point where like science has produced a test that are highly effective. We have fourth generation point of care HIV tests that can find usually within a few weeks of infection. that will detect the infection. We have PrEP, which is highly effective. We now have injectable PrEP that you only have to get a shot every six months, and there were essentially no HIV infections in people who got the shot. And then we know that treatment is highly effective, not just for prolonging the lives of people living with HIV, but also preventing transmission when people are treated for HIV to the point that they become undetectable. You can't find the virus. they cannot transmit the virus to others as well. So treatment also works as a form of prevention. So we have all these highly effective interventions and tools, but we're not seeing declines in cases. And I think that really speaks to a problem of implementation. And I'll show you just a couple examples of some of the implementation channels. So this is some data from two of my studies, the SMART study, which had over 1,300 teenage gay and bisexual boys in it, you can see in the blue line, an earlier study called Guy2Guy, which was a text messaging-based intervention, we see that in the sexually active teenage gay and bisexual boys, only about one in five have ever had an HIV test in their lifetime. So these are sexually active young men. We know this is the second highest risk group in terms of new diagnoses. And only about one in five of them have ever had an HIV test in their lifetime. As soon as people turn 18, look, we're over 90 percent, according to the NHBS data, have had an HIV test. So there's a clear implementation challenge. We're not reaching teenagers with HIV testing, and we really need to figure out, you know, what are the barriers and what are the solutions to help improve rates of testing in teenagers? I mentioned PrEP, pre -exposure prophylaxis, medication that's highly effective at preventing HIV infections. If it's taken as a pill, it's a daily pill. If it's taken as a shot, it's once every six months. We have seen big increases. Here you can see data. If you're interested in HIV epidemiological data, AIDS View at Emory University is a fantastic resource. You can get maps of countries and states and counties, really great source of data. We have seen these substantial increases in PrEP uptake in the United States, but it's really not reaching necessarily the people who are at the highest risk. So when you look at Black or African-American people, they represent 38% of HIV cases in the United States, but only represent 15 % of the people who are taking PrEP in the United States. Similarly, Hispanics represent 32 or a third of HIV cases are only 18 % of the community that's taking PrEP. So white people represent 24% of HIV cases and represent 63% of the people who are taking PrEP. So there's some real disparities and inequities in terms of how our HIV services are being delivered in this country. And so implementation research is really one of our ways to figure out, like, what are the barriers and solutions to addressing these implementation challenges. And, you know, one way to think about it is we have these interventions, we have treatment, we have PrEP, nearly 100% effective. Of course, nothing is always 100 % effective, but fairly close to 100% effective in terms of preventing transmission. If you think of any intervention that's that effective, then you think of, say, 50% of clinics decide that they're going to offer PrEP. And actually, that's not so far off, at least in the early days of PrEPs. Like health departments, for example, we were only seeing about one in five health departments for the first few years offering PrEP. And then within those clinics, say 50% of the providers decide that their clinic is offering it, but they're not going to offer it to their patients. Then you have the clinician offer it, but only half of their patients decide to take it. And then maybe only half of those patients keep taking it. And actually we see the average duration of oral PrEP people's use is actually tends to only be a few months. People go off it actually fairly quickly, despite it not having side effects or very many side effects. So if you multiply 100% effective intervention, you cut it at 50%, 50%, 50%, you get a 6% population impact. And these are all challenges with implementation of this highly effective intervention. And so implementation science is asking the question, what's not happening? Why is it not happening? How do we get it to happen? How do we know? How would we even know if it's happening in terms of intervention delivery? And it's really about pulling out this black box of saying, we have these effective interventions, we want to get to 100% population impact, but we need to be a little more explicit in terms of our understanding of what's happening and the barriers and facilitators to actually the delivery of this highly effective intervention. So answering that question of being a little more explicit about how delivery is happening is really the charge of implementation science. So I'm going to kind of start with the takeaways of my talk. So I'm going to spoil the rest of the next half hour and just kind of tell you some of the lessons that I've learned, and we'll come back to them. One of the challenges is there's a lot of this very commonly quoted statistic, but it It actually takes 17 years from a health innovation to actually reach routine practice. And only a small percentage of effective health interventions actually ever even reach routine practice. So we take a very long time from discovery of a health innovation before it's getting delivered in practice. We need implementation strategies for health systems to improve the reach of effective interventions, fidelity, sustained delivery of them. We need to understand how health systems work, public health systems. clinical systems. And we also know that patients and consumers, we need to address their needs as well in terms of, do they know about the intervention? Do they know how to access it? Do they know how to pay for it? Do they know, are they motivated to use it? Are they motivated to sustain their use of it? If they want to discontinue it, do they have a strategy of how to discontinue effectively? And so, you know, implementation science in its early days really tended to focus mostly on health systems. A lot of the work came from VAs, Veterans Administration Clinics, which is a closed kind of system, has a lot of advantages for understanding how to implement something. And then as implementation science has grown, it's also focused more, I would say, as well on patients and consumers and their understanding. And we published this paper in 2024 in implementation science on this concept of adjunctive intervention. So we really classify things as implementation strategies. How are you delivering in the system? Adjunctive interventions are really how do you get consumers and people who are going to use that intervention to want to use it, to understand how to use it, to benefit it. And, you know, if you're trained as a behavioral scientist, a lot of the theories that we have in behavioral science is about how to change people's motivation, how to instill self-efficacy in using a health intervention, many of those also work within health systems, right? How do you get clinicians to feel motivated to deliver an intervention? How do you get a health system to prioritize a particular innovation? I'm going to talk more about implementation science. I'm going to get into a little bit of the jargon. One of the things I'll say is if you're interested in learning more about implementation science, I co-lead the Implementation Science Coordination Initiative, which is a national resource for folks who are doing HIV implementation science in the United States. And we have tons of trainings and videos and handouts and tools. I'm going to show something from a logic model in a second. We have a logic model builder. So feel free to check that out and go. And there's a lot of free resources that are available to everyone on that website. So if I catch your interest in something, but you're like, wow, you blew through that really quickly, go to the website. You can learn more about all of these concepts on our website. So some key definitions as I talk about my own implementation research, there's a lot of jargon in our field, but just to define a few things. So implementation science is really the scientific field of studying methods to promote the adoption and integration of evidence-based practices, interventions into routine clinical and public health services. So that's the scientific field. We're studying methods. Implementation research is often really more about the scientific study of the particular strategies. So you might do an implementation research study of what are the barriers to implementation or what are the strategies that might improve implementation in practice. And then strategies, we use this word in a very precise way to mean approaches for techniques or methods to enhance the adoption, implementation, or sustainability of an evidence -based intervention, program, or practice. So I'm going to use, sometimes I'm going to be talking about the effectiveness of an intervention, and other times I'm going to be talking about the implementation strategies. The strategies are about how you deliver the intervention. Put in another way of saying it, the innovation, the practice, the policy is the thing. effectiveness research looks at whether the thing works at improving health so say the thing is a pill to lower your cholesterol the pill or the statin is the thing effectiveness research is a study where you're randomizing people to get the statin or a placebo and which one lowers your cholesterol better and if the statin works better it's effective so that's an effectiveness research Implementation is just delivering the thing, doing the thing. Implementation research helps to understand how to help people do the thing. Implementation gaps are where, when, for whom the thing is not being done. Implementation determinants, we talk about that as the context, the barriers, the facilitators, the conditions that make it harder, easier to do the thing. Strategies are the actions we take to do the things, and outcomes are how we know how well or how much we're doing at doing the thing. So these are some kind of definitions. I think the big thing to take away from this is the difference between the thing and the strategies or the effectiveness of the thing and the effectiveness of, say, the strategies. So we have the thing. We study determinants. This is often something you might do early in implementation research. What's getting in the way of helping people do the thing? What's helping them do the thing? What are the strategies that might improve the delivery of the thing? And then what are the outcomes that would tell us, you know, what percentage of providers are doing a prescription? What percentage of patients are filling that prescription? Those would be the implementation outcomes. We're not looking at whether the thing works anymore. We're just looking at how it's being delivered. IS loves our theories, models, and frameworks. In fact, we actually call them TMS because we have so many of them. There was a review recently done, but there's actually over 150 theories, models, and frameworks that have been described in the implementation research literature. Fortunately, in this excellent paper, they kind of broke them down into sort of clusters of theories. And so it's really the models that would describe the process of moving research into practice. Many of you might be familiar with EPIS, Exploration, Preparation, Implementation, Sustainment Model. Then there's the things that tell you about the context, the barriers or facilities. We call those determinants frameworks. A really widely used one, we use it a lot, it's called CFIR, the Consolidated Framework for Implementation Research. Then you have all the classic theories. If you're a behavioral scientist, you're thinking about stages of change and things like that, that are the classic behavioral therapies that are theories that are very relevant to implementation as well. We have some implementation-specific theories. So, like, ERIC is one around different types of strategies that you can use for implementation. And then you have your approaches to evaluating how your implementation project is going. One that's very widely used, I use a lot, is called RE-AIM, which is really about the reach of the intervention, the effectiveness of the intervention, the adoption of the intervention, et cetera. So it's an acronym. So just as you're kind of thinking about if I want to learn more about implementation science, sometimes it gets a little overwhelming because you see all these theories, models, and frameworks. How do these even fit together? We developed at Northwestern this implementation research logic model as a way to sort of also put this all together. And on our website, we have a logic model builder. So if you're interested in designing an implementation research study, you can use our logic model builder to sort of build out the study, and it'll actually output graphics for you that are, like, ready to go into a grant proposal. And actually, several NIH requests for proposals have suggested that people use our logic model builder as part of their application. So it really lays out first, like, what are the barriers or facilitators around implementation? then what are the strategies? And these are from ERIC, the sort of big class of the big domains of different types of implementation strategies. I find ERIC to be particularly helpful when I'm thinking about studying the implementation because it does lay out pretty much all of the options you might have. Not all of the options, but many of the options you might use. So you might not, I mean, everyone starts with training, right? I have a problem. There's not enough PrEP prescriptions. We're going to train the providers to do PrEP prescriptions. Training, we call it the train and pray. We're going to teach people to do something and we're going to pray that they're going to do it. That is probably the most widely used implementation strategy. But there's other things you can think about, like interactive assistance, supporting clinicians. What are the financial strategies that might support implementation? And then you have the innovation, the things, the pills, practice, principles, products, and then you have the outcomes of the implementation research project. So that kind of helps put it all together. And as As I mentioned, on the ISCII website, we have some trainings about how to develop a logic model. We have this interactive IRM tool that you can use to build a logic model for a bunch of different types of studies. So that's my Implementation Science 101 in 10 minutes. Now I'm going to talk a little bit about how I've applied it in my own work. So as I mentioned earlier, a lot of my work is my intervention work has been around using digital technologies to train, motivate, give skills to young people to improve their sexual health. This has been a big, at least as it relates to HIV, a substantial investment from the NIH. So actually, in NIH Reporter, which you can't go to today because it's down, I think, but if you ever were to search, they have one category called telehealth, which is actually their category for anything that's like mobile technology, digital technology. And if you combine telehealth and HIV, you'll see that NIH invested $108 million just in three fiscal years. So we're talking about over $30 million a year in development and studying the effectiveness of digital HIV interventions. Huge investment. We see that as the sort of beginning of the process, right? You apply for an idea to test an intervention, and things might get into this intervention science loop, which is I'm developing an intervention, and say it doesn't work. You know, you do the trial. It's not effective. You might say, well, that's because we needed to add this other component. We'll go back to the start. Some things get stuck in this loop, and that's good because we don't want to scale them because they don't work. Maybe we need to keep optimizing. Then you say, okay, it's effective. And a lot of times in HIV, things move into these compendiums, these lists of what are the effective interventions. They met this criteria. CDC has a list of criteria if you want to be a best-evidence HIV intervention. You must have designed your study with this rigor. The results have to be this strong. You get into this compendium. CDC has one. HRSA has one for HIV services. And there's 43 digital HIV interventions in the CDC compendium for HIV prevention and 14 in the HRSA compendium for HIV care delivery. So now you're in this compendium. And in the ideal scenario, now you're in the compendium and now everyone's going to start using your intervention, right? It's on the list. So all the clinics are going to start delivering it and you start delivering this digital intervention. It's reaching patients and it's having the outcome that you would hope it did. Who votes that this is the way things work in the real world? No, what we see is a lot of challenges, a lot of cones, a lot of breaks in the road. And that's really the job of implementation researchers to say, like, there are all these challenges along the way. How can we identify those challenges and how can we create solutions? So if you work at a university and you develop this digital intervention, how do you get it out of the university? right? Like, is IU going to deliver this digital intervention to everyone around the world? Probably not, right? It's not, IU's technology platforms were not designed for delivering things in that way. They're designed for students and research. So how do you make it scalable? How do you make it, maybe it has to be available in multiple languages. It has to be secure, maybe in a different way. So those are implementation questions. How do you maintain the technology, right? Like, I did this sex education program. It's highly effective, but now there's a new browser that it doesn't work with, and everyone decides they want to use that browser, and now nobody can use it anymore. You've got to update the technology. You've got to keep maintaining it to make it continue to be secure, which often means updates as we find about insecurity or vulnerabilities in different technologies. You also might be in a situation I was in in the middle of a large study of HIV prevention in adolescents where the FDA approved PrEP for teens right in the middle of my trial. So we had all this content that talked about when you're a little older, you might consider getting on PrEP. And now they can get it today. And so we have to, obviously, we have to update the content because we're not going to falsely inform people about an intervention. So you can't just set it and forget it and put it up on a website and it's going to take care of itself. There has to be maintenance. How do you train organizations to deliver it? How do you reach the end user? How do you support recipients to learn about the intervention, want to use it? These are all implementation research questions and ones that implementation science can do a lot to address. The problem, as I see it, and we wrote about this in this paper in current HIV AIDS report about, we call it the package could not be delivered, the state of digital HIV interventions in the United States, is that we can solve all these problems. And there's actually a lot of fabulous implementation research looking at each of these cones along the way. But there's still this chasm, which is that our funders, our health system, is not designed to set up to support the delivery of them. So community organizations often can't get funding to deliver digital interventions. There is no CDC funding to deliver, to support the delivery on a national level and of an effective digital intervention. So we still have some policy problems that we need to push our public health agencies to address because there's only so much researchers can do. And we have to be realistic about that, right? Like we We can't promise to solve problems that are actually inherent within our health system. But there's a lot that we can do. So I'm going to give you some examples of some implementation research that I've done with the Keep It Up intervention. And this was funded by multiple divisions within the National Institutes of Health as a hybrid type 3 cluster randomized trial. Now, I'll talk a little bit more about hybrid trials later if there's time, but a type 3 trial is really focused on how do you implement it, but while we're implementing it in practice, let's just see if it still works. So you're getting a little bit of effectiveness data, but you're really focused on implementation. Keep it up. This intervention has been a long journey for me. I actually got an R34 in 2007. So talk about that 17-year path. Like, this is real. So, you know, and I was trying to move as fast as I could. I was not delaying in any way. But in 2007, I got an R34 to develop a digital HIV prevention intervention for young gay and bisexual men. We did a lot of focus groups with diverse young men. We did focus groups or individual interviews with staff who delivered HIV testing services. One of the things that was very cool is that came out from the young people is they were like, we do not want an HIV intervention. where you say, session one, HIV is a virus, and here's how it's transmitted. Session two, here's how condoms work. Session three, we need this about our lives. We've got a lot going on in our lives. How does HIV prevention fit into our lives? We don't necessarily need the facts. We kind of already know that. Let's skip to the context and the realities of like, should I use a condom with my boyfriend? We were talking about that at breakfast today. Those are like real questions that people have. It's not, should I use a condom? It's like, should I be using it in this particular setting? We published the results of that. It showed a reduction in condomless sex compared to a very active control condition, which was sex education. So we did sex education in one arm, and we did this very motivational, interactive digital intervention in the other. We saw reduction in risky sexual behavior in the keep it up arm. I then applied for an R01 and didn't get it. I was like, okay, we are ready to move this on, people, let's do the full effectiveness study. And it had to submit it several times. And it was like, well, we prefer you use this questionnaire than that questionnaire. It was like a lot of nitpicking, which is how the review process works. But in the meantime, the city of Chicago health department said, we're looking for homegrown interventions that address young gay and bisexual men. We don't have interventions. There's no evidence-based interventions. Does anybody have anything? I said, well, I just developed this and we have some evidence that it works. And so they actually funded our community partner to deliver this as a service in the city of Chicago. We enrolled over 600 young gay and bisexual men, got the intervention, no control group, but we studied it. We did the evaluate. Our role was to deliver the technology and to do the evaluation. We actually found it worked better when it was delivered in the community than what was delivered by us through the university. I then finally got the R01 I'd been wanting that NIDA and NIMH funded to do a three-city effectiveness trial where it was delivered through community-based testing sites in New York, Chicago, and Atlanta. And it actually had one of the first studies of its kind to have a biomedical endpoint. So we actually did rectal and urethral STI testing in the study, and we did it through the mail. So we actually mailed people kits. They self-swabbed themselves. Actually, there was some great work at IU that was happening that helped us realize that's something that we could have done, that people could self-collect. And this ended up being the first digital study in the HIV space that showed effects on a biomedical endpoint. So the guys in the Keep It Up arm had 40 % fewer rectal STIs than the guys in the sex education arm. So highly effective, one of the first studies of its kind to show effectiveness on a biomedical endpoint. It was then delivered as a service again through some funding from the Veeb Foundation in Jackson, Mississippi. Service organization in Jackson, Mississippi wanted to deliver it. They sought out funding to get it, and we were like, sure, we'll help you deliver it. So we did another implementation study. And then the question was, okay, so we've shown this works in several different ways and several different delivers. How do we implement it? And I'm fortunate to have a lot of inroads with leadership at CDC, Division of HIV Prevention, and I was like, let's, okay, we really have to figure out how to get these things implemented. And they're like, no, you need to go figure that out. Like, write another grant, study the implementation. And so the main study that I'm going to show you results from is a large implementation study looking at how to implement these digital interventions. Before I get into that, I was just going to show you a little bit about what Keep It Up includes. And Keep It Up is informed by the information, motivation, behavioral skills theory of health behavior change. It includes a web series. So there's like an online soap opera where you're following a group of young gay men. It's designed for people who just tested HIV negative. That's why we call it Keep It Up. They just got tested. They tested negative. The goal is for them to keep up their negative status. It was really informed by the reality that our community partners said, we have no resources to do risk reduction with guys who test negative. When someone comes in and tests negative, we say, congrats, you're negative. We'll see you again in six months or whenever you come in for a test. And so we were thinking, well, let's develop something online and they could at least send people to that as a way to promote prevention. And it has school setting, a lot of interactive exercises. is I'll show you some pieces of it. If you go to kiu.northwestern .edu or scan that code, you can actually see like some of the videos and content from the Keep It Up intervention. And one of the things that is really key in implementation research is the concept of adaptation and how you adapt things. And so Keep It Up does not look the same way it did in 2007. So in 2007, you know, it had like graphics that look like this. It was like very low res videos. I mean, we frankly shot them on like a flip cam in my dining room at my house. You know, it was like my administrative assistant is holding the microphone. You know, it was like we had a very small budget. We, I think, did a great job with what we had. But, you know, we had to update it. We had to keep it relevant. We had to improve the quality of the content. And so I was just going to share a little bit of it with you. But these are the different modules in the intervention. And the young people that we talked to when we were developing it, as I said before, said, we don't want just the HIV education. We want this to be integrated in our life. So each module is actually a different kind of context or setting in the lives of young people. So it's about how does HIV fit into dating? What if you're hooking up with somebody on the internet? What if you're at a bar and you use drugs or got too drunk and you're now trying to navigate having sex with somebody? how do you integrate prevention into those different settings? And so that's kind of the larger content. As we've been adapting and keeping it up current, one of the things that's been really helpful for us, and I credit my colleague Dennis Lee, who actually wrote a paper about this, is that we really, for all of the modules, we really have a crosswalk of how it fits into our behavioral theory of the information motivation behavioral skills and how each module addresses some of those components so that when we're updating the platform when we're reshooting the videos we're not just taking the exact same script in the first video and just shooting it with a better camera we are updating it to be a little more current but anytime you are making updates you have to have a sort of a belief about the underlying theory the underlying mechanism of action so you keep it relevant to that. We use a framework a lot that's used in eHealth by my colleague David Moore called Trials of Intervention Principles, which means when we're making updates, we sort of classify things as these are core components that should not be changed, and these are things that must be changed, like, you know, the browser doesn't work anymore. If you don't update it, it's not going to work, so you must update that. Or there's a change in medical information, and you must make an update. Then there's other things like how we make people feel vulnerable in a way that would want them to engage in a prevention program. Those might stay the same as we refine and continue to update the intervention. So I thought I would just show you some examples of some of the videos. One of the things that I absolutely love is man-on-the- street videos or person -on-the-street videos. I include them in all of my interventions. It never lands the same with actual actors. I've worked with so many production companies who, as soon as I say we're going to do person on the street videos, they're like, OK, well, we'll do a casting call. We'll hire the actors. And I was like, no, this is we're on the street with my dog. People stop to talk to pet my dog. And we're going to ask them questions. And they're going to sign a consent to be in the video. And the things that they say are just so powerful that I don't think there's any way to recreate them with actors. So this is the same module in Keep It Up 1.0 in 2007 and the new version in the current version. How many examples in that video where you could see, like, if I had actors doing it? I mean, that one when the guy turns and says, that's a stalker. I love it. And these two things are just amazing. So, you know, that's part of our theory is that, like, you connect to them. You want to hear what they're saying. And these are the first videos that people see in the intervention. And so, again, they get started and it's not HIV is a virus. And here's how it's transmitted. It's hearing from other people like them talking about the realities of being in relationships, why you'd want to be, why you want to be single. We're not your mother. We're not going to tell you to lock it down with your boyfriend. There's a lot of different ways that people seek fulfillment. And we're going to try to help you understand how to address all of those forms of fulfillment in the context of also addressing HIV. This is the more refined, newer version. Maybe better, maybe not. You can see it's different people talking, but you get really the same flavor. The production quality is a little better. The video quality is a little better. But, you know, like we couldn't just hire actors to say the scripts of what those other guys said. It wouldn't certainly land the same way. One of the other things we built into this is an HIV transmission risk calculator. This was a new approach. In the Keep It Up 1.0, we gave people a lot of facts about the risks of different sexual behavior. We really, as technology is developed, there's ways to do things in a much more interactive way now. So you can actually click on these things, and it'll give you your epidemiological risk of HIV, as we've confirmed with the CDC, as the per-act transmission risk. So you could say, like, I'm HIV negative, and I'm going to put my eggplant in someone's peach, and it'll tell me what my risk of HIV transmission is. then I might say, well, I have an STI, so that actually significantly increases my infection risk. My partner is undetectable. That's going to lower the risk. We're going to use a condom. You can see the risk. I'm going to take PrEP. And we actually find people spend a fair bit of time on this calculator because we have data to see how much time they spend on each page. And they actually do a lot of like, oh, wait, so I guess if I'm going to do this with this type of person, maybe I should instead do that because my risk would be much less that it might still, you know, be pleasurable. And that's what it's all about is we don't want people to sacrifice their pleasure, but we need them to reduce their risk or want to encourage them to reduce their risk. So as I mentioned, there's these compendiums, Keep It Up was added to the compendium of, it was one of the first digital interventions added to the CDC compendium of evidence-based HIV prevention intervention interventions. And then our question was like, okay, so this works. We've shown it works in a bunch of things. How do we implement it? And so that was really the focus of the Keep It Up 3 .0 study. And so we thought, what are ways that interventions get delivered in the United States, HIV prevention interventions? So the most traditional way is a health department or the CDC puts out a funding announcement and a bunch of community organizations apply and say, fund us to deliver this intervention? And that's the sort of classic approach. We call it the CBO kind of based approach. How are technology interventions delivered or how are technologies delivered? Like you don't go to your local health department to download an app, right? You just do it on your phone yourself. You can do it at two in the morning. You can do it whenever you want. And we call that the direct to consumer approach. So what we did is we identified 66 U.S. counties that had very high levels of young gay and bisexual men. And we randomized them two to one. So two times as many counties were randomized to the community approach. And then within those counties, we sent out announcements saying, we have money to give you if you implement Keep It Up as a service for young gay men who come in for HIV testing. So we're going to give you $40,000 to implement this over two years in your organization. And we're going to do most of the, we're going to deliver the technology. we're going to train your staff, we're going to do all that. Literally, what we want for you to do is when someone comes in and tests negative, if they're a young gay man, offer them keep it up, and we're going to give you some money to do that. So we thought that's very pragmatic. That's kind of the way health prevention interventions are often delivered in the United States. The other approach was, well, we're just going to do it all from Chicago. We'll do advertising on Grindr and other apps. We'll recruit people. We'll mail them an HIV test kit through the mail. We already showed we could do that. We'll mail them an STI test kit. We'll deliver the result. We'll refer them to CARE if they test positive. We'll deliver the intervention. We'll collect the outcomes. And our question is like, well, which works better or which works better in different types of ways? And one of the things that you'll see in implementation research is a lot of times you have a lot more outcomes than you might have in a clinical trial. Clinical trials like, did the cholesterol go down? How many HIV cases were there? That's really the only thing that matters. In implementation research, different people, different stakeholders care about different things. Some people care about the cost. Some people care about, are you reaching the most high-risk people? Some people care about fidelity. So you'll often look at a lot of those different outcomes, and we're interested in those and comparing these two approaches. What I'm not going to talk too much about is the fact that this was my dream study. Literally, like my whole career had been building to do this study. I convinced NIH to give me this enormous grant, including me telling them, you give me the money, and then I'm going to do a grant competition for other people to get money to deliver the intervention. I can't even tell you who those people are yet, because I haven't done the request for proposals yet. It was like the NIH was, you know, when it got a great score, they were like, we don't, you want us to give you money, and then you're going to give it away to other people, and we don't even know who those people are yet. I was like, exactly. So this was my dream study. It was really designed to address questions. And then COVID hit. And we had just gotten the site selected, funded, trained, and then their clinics were closing and their clinics were reopening and they had capacity restrictions. So we continued along. I'm not going to go into all the details of how the study had to be salvaged. But there were some limitations that you have to sort of roll with. We still learned a ton about how to implement an intervention like this. So our primary outcome was cost per infection averted, because that includes, it sort of combines information about cost, it combines information about effectiveness, it also, you can invert more bad outcomes in people who are at higher risk. So it also integrates information about the riskiness of the groups that are enrolled using these different strategies. So that was our primary outcome. Our secondary outcomes were really about the context. Like, why might some community organizations do a better job of implementing than others? Maybe some do a better job of enrolling people or enrolling people that are higher risk. Some might do a better job at fidelity and delivering the intervention. And so we did interviews with these 22 community organizations over time to just ask them about, like, before they got started, tell us about your organization. How much leadership buy-in is there for this? Is that the only person who likes it, is the leader and everybody else on the staff thinks we have a lot of better things to do with our time? Or is the whole organization excited about the delivery of the intervention? And so we use the CFIR Consolidated Framework for Implementation Research Guide. They have an interview guide to collect that information from organizations. This paper recently came out in AIDS and Behavior. And we did look at using this interesting analytic approach, which I'm not an expert in. But we identified that some of the barriers were around the self-efficacy of the staff at delivering it, like whether people were still feeling confident or not that they could actually refer people to the intervention, their motivation. Staff turnover is a big one. We really had to optimize our systems for the fact that there's so much turnover in these community organizations. And so how do you train people quickly? How do you have things at people's fingertips when they leave and somebody else comes in and they know how to find the way to enroll somebody into the intervention? Some of their infrastructure capacity were important predictors. So if you want to read more about why some community organizations did better than others. This is a great paper. We put together a ton of materials, but we didn't want to just do train and pray. We didn't want to do like one training and then you know how to do keep it up. So we also put together this dashboard that this is a highly sped up video of because the video is quite long. It's on our website if you want to see it. But it showed it's a dashboard that really organizes like, are you a project director? Are you a coordinator? All you're doing is recruiting. I just need to put names in the system. I don't actually never need to be able to follow them after that. Here's a list. Here's your to-do list. You come to the website. You get to work in the morning. You log into the thing. Here are the people you need to follow up with. So we really tried to facilitate the practice of the delivery of the intervention so that it was just at people's fingertips. And they didn't actually even maybe necessarily have to know that much about Keep It Up in order to successfully enroll people and track them through the intervention. Again, you can see how we developed this platform and more about it on the Keep It Up website. Here's the primary outcome paper, which actually just came out, I think, a few weeks ago. We did costing analysis. So we had a whole team of health economists who did micro costing. They interviewed each of the clinics to understand some of the costs that went into delivering. So we gave them $40,000, but maybe it cost them $100,000 because they were using a lot of other in-kind resources. Or maybe we gave them $40,000 and they only spent a little bit of it on the intervention delivery. And so we did micro costing with all of the clinics, as well as for the direct -to-consumer approach. They interviewed the staff in Chicago. We were interested in demographic differences, given what I said about differences in the HIV epidemiology in the United States. This is comparing the direct-to-consumer to the CBO. You can see the direct-to-consumer approach enrolled more than twice as many participants. So 1,468 young men enrolled directly in the approach we used from Chicago, 656 participants enrolled through 22 community-based organizations. So this was more efficient in terms of reaching people. There were some differences in terms of the age. So the age split in the DTC was more balanced, whereas they were slightly more concentrated in the 24 to 29-year-old group for the CBOs. The CBOs did a better job of recruiting Black and Hispanic participants than we did in the direct-to-consumer. So there was a higher proportion of minority participants in the community-based approach. Now, when you start multiplying these out, though, you actually see the TTC recruited more Black participants because they recruited more participants overall. It was just a higher proportion in the community-based approach. And then there were some differences that the DTC actually did a better job of recruiting bisexual participants. So one of our primary outcomes was how we did in terms of increasing PrEP use. Because of the challenges of COVID, originally we were going to do a one-year follow-up. We had to limit that to just a three-month follow-up because we needed to have more time in the field. And at baseline, the arms were actually quite similar. The community group just had a slightly higher rate of guys who were already using PrEP. At three months, both arms increased in their use of PrEP. That increase was bigger in the community arm. And the way we interpret that is that Keep It Up does a good job of motivating people to get on PrEP. But if you're already embedded and connected to a community organization, maybe where they can actually prescribe it to you and maybe even give you a starter pack right there on the spot, it's a lot easier to do uptake than if now you decided you want it. Now you have to find a clinic. You have to get yourself there. So we think it works in both arms, but there's a lot of benefits to bring it in the community because people can get the prescription directly. And we also found that the intervention effects were larger in people who actually finished the intervention. Of course, not everybody finishes things. So we did this model of HIV infections averted using rectal gonorrhea. There's an approach to convert rectal gonorrhea rates into estimated what would have been the HIV incidence in the cohort. We use this modeling approach to compare the number of infections averted per 100 people years in both arms. And then we use the cost data that we collected to look at cost per infection averted. The CBO arm cost about a million dollars to avert one HIV infection. whereas the direct-to-consumer costs about $170,000. This is not per person. The per-person cost is in the hundreds. This is about the cost of averting an HIV infection. So we see that going through the community organizations is tremendously more costly, not just in the money we were giving out, but the other in-kind costs that were brought to the table in the delivering of the intervention. in mind, though, these clinics were opening and closing. They had capacity restrictions. We estimate from our experience in Jackson, Mississippi, that the cost is significantly lower for delivery, which, of course, then brings down the cost for infection averted outside of COVID. So we actually think it's probably a lot less costly than that. But I think the relative ratio of cost is probably true between the two arms. Because also, like, our staff sometimes couldn't go out of the office because of COVID. So we were experiencing similar issues. But let's put this in context. So the CDC estimates that anything that costs less than $494,000 per infection averted is cost savings, actually saves the health system money given the lifetime cost of HIV care. They also say that something that is cost effective at less than $100,000 per quality adjusted life year. And so PrEP, for example, lands around here, at least used to, I think the cost has also come down. But that suggests that certainly the direct -to-consumer model is for sure cost-saving to the health system and definitely then also cost-effective. I think whether the community-based approach is also cost -effective would require additional data on quality of life and stuff that we don't have. Also putting this in perspective, this is CDC estimates of the cost per infection averted for behavioral interventions in PrEP in high-risk heterosexuals. We're talking at almost $25 million for the cost per infection averted for PrEP in high-risk heterosexuals, or over $15 million for averting an HIV infection using a behavioral intervention in high-risk heterosexuals. So while these numbers may sound high in the Keep It Up intervention focused on men who have sex with men, you can see there's just a drop in the bucket. And I don't think anyone would say we shouldn't do anything about HIV and heterosexuals in our country, right? So clearly, we also have to contextualize these cost data. For the sake of moving on to questions, I think I'm going to skip through some of the other slides. I think they're, you know, can be available to people if you reach out to me. I also, you know, we were talking about SMART studies earlier. I also led a multilingual intervention for teenage gay and bisexual boys. But I'm going to just wrap it up. I'm happy to answer questions about that, but just so we have time for questions. And thank you. This is our newsletter for the HIV Implementation Science Coordination Initiative, and that's the website again, which you can also sign up for the newsletter if you're interested. So, questions? Thank you, Brian. That was an excellent talk. Thank you. I'm just curious to learn more about the implementation strategies. I went talking implementation research. What were those? And what were your implementation outcomes? I saw your effectiveness outcomes, which are secondary and type three. So, I'm just curious to know what were your implementation strategies? I know you mentioned train and pray, which we always start with. It's step one. Yeah. We have to do it. Yeah. I hear you mentioned practice facilitation, so I was thinking, can you talk a little bit more about that and what was the implementation outcome, like your primary outcome? Yeah, yeah. Great question. So in this particular study, we did use cost per infection averted as our primary outcome because we felt like that integrates some important implementation data cost and also reach and reach to high risk populations, which you the cost per infection averted is almost always lower if you're reaching higher risk people because there's going to be more cases in high risk people. And so if one strategy reaches the highest risk people, it's probably going to have a lower cost for infection averted, unless it's incredibly costly. So we felt like that actually wrapped up a bunch of different outcomes that we were interested in. Then we were interested in just using re-aim more broadly. So we were interested in how many people were reached using each of the strategies in the same time period and reached to key populations, Black, Latino, in particular, given the epidemiology of HIV. We were interested in adoption. And so adoption is very hard to define for the direct-to-consumer strategy because we were delivering it. But we were interested in understanding adoption at each of the sites. So they applied to us, right? So they had said that they wanted to do the program. And we, by the way, got more applicants than we could fund. So it's not like we've just funded all the people who applied. We had screened some people out or some sites out. But, you know, how many of them, once they were funded, actually delivered it and started routinely offering it to participants? So what's interesting about this study is I think it's different than when you think about strategies like using the ERIC approach, which we also did. And I can share a paper with you where we talk about the ERIC type strategies for the CBR. We had this sort of meta level question, which is like, what is the delivery approach? Is it direct to consumer versus community based? And so it's a little different than maybe you've already identified the delivery strategy, and now you're trying to optimize delivery using, say, ERIC approaches. Within each arm, we then had our implementation strategies in terms of how we delivered. So, like, we really encouraged community organizations to implement, like, an audit and feedback type approach. So we encouraged them to, and taught them how and did check-ins with them to see if we could help them further, use their own data to say like, okay, how many young MSM did you test for HIV this last two weeks? How many of them enrolled? Do you see differences by staff person, right? So one staff person did 25 HIV tests this week and 20 people enrolled, and another staff person did 25 HIV tests and one person enrolled. You might need to talk to those staff people, and maybe your one person could be a role model to the other person. So we encouraged them to use an audit and feedback type strategy. And then we did that facilitation approach of using the dashboard that really laid out, like, this is what you should do. And then we also had an online learning management system. So if a new staff member came in or at the beginning of the whole thing, there was a self-paced online learning system that they could go to learn. How do you create advertisement? So some of it was specific to keep it up, but some of it was like, how do you promote HIV testing to young gay men? Because if you're not testing enough of them, it doesn't matter what we have to offer. You need to get them through the door for testing. So we had, like, learning how to do outreach on social media to young gay men. We had, like, ads that they could collect and use. And so that learning management system was our approach. And we purposely did it that way versus, like, a Zoom meeting or something because we knew the staff turnover was so high that in these clinics that you just need to have people be able to come in and learn it whenever they need to. And then the last was the last piece. It'll come to me. But there's also another really good, if you're interested in digital health, my colleague Nanette Bembo just published a paper in Implementation Science Communication using the PRICE system, which is how to score implementation studies on how pragmatic they are across a bunch of different dimensions. And she scored it for both of the delivery approaches, which is also a paper where you learn a lot about the strategies because we talked about how pragmatic they were compared to like the way things are normally done. yeah thank you again for the the talk uh let me put it like in my point of view something like i have to tell you uh we in some countries we have a lot of problem about hpv something you know it's a virus and they probably say you don't the first thing we have to do don't have sex and didn't work, of course. Second thing, they have used condom in the work as well. So some countries like Australia, they start having the vaccine for men, for the girls and the boys. So it decreased a lot. They said that HPV is much worse in women than men. What do you think for the future? The PrEP will be the same because we have like this, you show the data, there has a window of age that you have this really increased number of, you know, positive. Do you think the future will be that? We will have this PrEP six-month, everybody for that population? Or do you think something? I think that would be lovely. I mean, I think that could be a game. I mean, that could end the epidemic if we really created systems that would allow and empower young people in that age group to get access to injectable PrEP. I mean, there's, like, almost no side effects. I mean, there were like very few cases in the study that became infected. One was like resistant to the particular. But, you know, we would literally probably almost eliminate new cases and young people if people got that shot every six months. But then you have like we have a Covid vaccine that was highly effective and people have a lot of beliefs about some kind of injection being put in their body. And now the government's telling you to do it. They trust the government telling them that they should get this shot. another vulnerable group that's been told by the government that they don't exist or that they should not exist. So I think that, and even if those sentiments weren't there, I mean, there also are just the real implementation challenges, like how do we get this out to communities? And so there is some very cool work happening with like mobile vans into communities. But I think we really need an all hands on deck approach to make that kind of radical change that it would take to have something like that work, which would be like social marketing, community norms, community health centers that people could easily go in, that you don't have to make an appointment three months in advance, but you can just walk in the door and get your shot. You can get your STI testing. So I think it's achievable. I mean, I really do think we could end the epidemic in at least in the United States and probably in some other countries it'll be much easier to do that have integrated health systems. But we have an uphill battle. to be honest here. That was awesome. I'm an epidemiologist. So this is outside of the scope of what I do. And I just found this so informative and well presented. Thank you for that. I had a question. I have two questions. One is like a very broad question, which is how did you conceptualize this career that you've made? And like, I'm astonished by your productivity too. Like you seem very normal the mascot published 365 papers that's unreal it's obviously like incredibly meaningful work and valuable work like when you're earlier in your career how did you how did you get going and get like what was the motivation and the like the strategy yeah kept you able to get where he planned yeah I mean a couple of things I say one is like I love writing I really do like I love writing I love writing papers I love reading my students papers and my mentees papers um so that helps a lot in writing a lot of papers um doesn't mean I always feel like writing but I do make it as part of my practice where I'm writing every week and I just really try to keep that up and it's so all the forces in academia and the world are designed to make us not be writing right now or in most of our career and like I do firmly believe that we particularly when I receive taxpayer money to do these projects that I have an obligation to share the results and share them in a timely way and I really I don't just say that like I really do believe that um that's obvious of what you've done too and I also think that I am very driven by the mission of what I'm doing like I really I get outraged by things and then I'm like I'm going to go do something about it. Like another example, my first grant when I was a young professor was from the American Foundation for Suicide Prevention to do a two-year study of suicide risk in LGBT youth. It took me 10 months to get IRB approval for my two-year study because the IRB was like, you need parental permission. And I was like, no, I don't. And here's the rules and here's how you can get along them. And then they were like, we don't like this advertisement. You can't use this word. You can't use that. And I was like, you know, I'm going to start studying this. Like and I actually learned a lot about ethics research and got an R01 to study the ethics of LGBTQ being in research. And so I think a lot of what I do is like always I'm thinking about like, what are the problems and how do I use science to address them? Like I can't I'm not you know, I don't work and I don't lead a federal agency. I don't have that. But I have science as my tool. And so I just like apply it to all the things that piss me off, which is an unlimited supply of things. One of your slides had like the, I forget, I'm sorry, I forget what you called it, but you had like circles within circles and it was like a hundred percent, 50%, 50%. I was thinking about, So I'm a vascular epidemiologist, and I study basically physicians' delivery of antiplatelets and statins and other guideline -directed medicines, which they don't do. But I sort of think of myself as like, that's where I stop. And then there's, what do you think about that? Like, you don't stop there. You seem to cover all the rules. I don't believe in science being a relay sport. I really don't. I think that maybe it works in some areas, but I just don't think there's somebody waiting to grab the baton to take it to the next level. And that sucks because I don't feel like that's how we're trained. And it means oftentimes you have to learn a lot of things that you thought you were done learning, and now you have to learn something else. But it also is incredibly rewarding to see something through from development to at least implementation research, if not eventual implementation. So yeah, I just, I don't, I think everything we're learning from implementation research is there's just not people to grab the baton or you have to find those people and you have to actively find them and then hand, maybe forcefully hand them the baton, you know, convince them to take it. They're not going to be out there looking to grab things and move it to the next level. So I do really firmly believe that. The last thing I want to say is I went through my last few slides very quickly, but I also have like a team of nearly 100 people, you know, that I work with. And so it's not just me doing all these things. Like it's a super collaborative environment. And so many of these projects are literally none of this would have been possible without this like amazing team of people I get to work with. So that also is and also makes it fun because they're cool people, too. Thank you for your questions. To be fair, you also built that team. Yeah, too, right? I mean, like that, those people didn't exist at Northwestern. You went to Northwestern and you created. Yeah. That's part of the story that it is about the players. And you've got a wonderful team. You mentioned Dennis. Yes. Catherine. Catherine. And Michael. On and on. Here at IU. Mm-hmm. Yeah. That also was part of the strategy too. So let's give Dr. Mustansky another round of applause. it was a wonderful opportunity to have him back to Bloomington. He said that he hasn't been to Bloomington in several years, but welcome back. And this is just a small thing to welcome you back. So if we can do a quick photo here, so you in the middle and you can, I don't know. there will be other opportunities to engage with Dr. Mustansky um 2 p.m uh cedar activity what's the room that's a room somewhere oak room oak room oh if you want more opportunities to engage with Dr. Mustansky come to the cedar thing at two; sex salon tonight sex salon fun at seven o'clock and where is that? The Bishop. The Bishop, sex salon seven o'clock; thank you so much.

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For those of you who do not know me, I'm Ellen Evans, the Chair of Kinesiology. Welcome to our event. This is the Distinguished Colloquium Speaker Series and Events. I'm happy to be here, very thrilled that Dr. Michael Joyner, Mike, as he's referred to, I hope that's okay, is here with us today for our discussion. But before we get rolling, come on in. Don't be shy. There's a couple chairs over there, standing in the back, standing's always good. Appreciate that. I just want to give a shout out to two people instrumental. One is over there taking pictures, and she just grimaced a little bit. Thank you for your work, Caitlin. And Dani’s over there hiding behind the corner. These two individuals have a lot to do with pulling off our wonderful events in terms of organization, communication, et cetera. So thank you for your efforts. The other two individuals that have really helped me would be Blair, who will be up here next to give an introduction, and then Robert Chapman sitting quietly there in the third row in terms of bringing Dr. Mike Joyner to our campus. So without further ado, I'll turn it over to Blair, and he's going to give a nice introduction before we get rolling, and here we go. Thanks. All right. Thank you, Ellen. Although Mike told me to keep it short just now, it's hard to keep what he's accomplished short. So it's my pleasure to introduce Dr. Michael Joyner as our distinguished speaker today. He's a renowned physician scientist based at the Mayo Clinic in Rochester, Minnesota. He's been at Mayo Clinic since 1993 as a consultant, and he holds the title of the Frank R. and Sherry K. Wood Professor of Anesthesiology and serves as a professor of anesthesiology with a joint appointment in physiology and biomedical engineering. He has held a variety of roles during his time at Mayo Clinic, but one of my favorite positions that Mike lists on his biosketch is that he was a lifeguard for the city of Tucson in Arizona. Dr. Joyner received an undergraduate and medical degrees from the University of Arizona and completed his residency in anesthesiology and research training with Dr. Shepard at Mayo Clinic in the early 1990s. His research portfolio spans integrative human physiology with a special emphasis on how the human body adapts to complex physiological stressors such as exercise, hypoxia, standing, orthostatic stress, and blood loss. In addition to this work, Dr. Joyner took a prominent leadership role during the COVID-19 pandemic, and he led the United States Expanded Access Program for Convalescent Plasma. Dr. Joyner is recognized internationally for his scholarship, teaching, and mentorship. His laboratory has been funded continuously by the NIH since 1993, and he has contributed to hundreds of peer -reviewed publications and received countless awards based on his research. When adding up his publications, Iran out of beads on my abacus. He's got an astounding 415 original research publications, 107 invited reviews, and 170 invited commentaries and 21 book chapters or books, and that was as of this summer, so that number has grown. Additionally, Mike has also written the 127-page non-fiction book, Michelle the Archangel. It is available on Amazon for $9.58 and is a 4.8 out of 5 stars. In regards to his mentorship, Mike has trained over 100 undergraduates, high school mentees, and rotating medical students. He's also trained 36 postdocs that now run independent labs at academic, government, or industry institutions, and he received the Bodell M. Schmidt-Nielsen Distinguished Mentor and Scientist Award from the American Physiological Society in 2014 for his outstanding mentorship. I was lucky enough to be one of those postdoc trainees, and Icon thank one of his former University of Arizona track teammates for helping me get in contact with Mike. I reached out to Mike in the winter of around 2011, inquiring about a postdoc position, and immediately got a quick email response back from Mike, Blair, this looks great, more later, which was typical. So a couple of years after my postdoc, I find out that he opened this email quickly because he thought the email came from one of his former track buddies named Blair Johnson, who apparently was a wild and crazy guy back in college. And I was interested to see what he was up to nowadays. So Icon thank your former colleague, track, he made for that. And so without further ado, it's an honor to have Dr. Joyner here with us today. And he's going to speak on exercise and experiments of nature. The nonfiction book, Michelle the Archangel, has a track and field element to it, among other things. So does anybody know why Inset the price on Amazon at $9.58? Dr. Chapman knows. The hundred yard dash? We've seen a world record of 9.58 seconds. [Unintelligible] pole vaulter. All right, so we're going to talk about exercising today. And here's the overview of the talk. We're going to talk a little bit about the word epistemology with the progress Krohb Principle, Claude Bernard, and Passive Experiments. Both Krohb and Bernard are foundation figures in physiology, and we're going to spend a lot of time on experiments in nature, talking about these and transporters that we did in London after World War II, to kind of set the stage for that, and talk about why this topic now, and talk about these sort of passive experiments, and exercise and give you some reflections so does anybody here uh anyway we'll get that started to take home messages knowledge comes in many flavors tools to gain knowledge are too little than that knowledge per se so you hear a lot about randomized before trying to provision through freedom and you got to be careful because if you only can do one type of experiment you get into a hammer-and-nail sort of thing. Insight is a puzzle. Information coming from all sorts of sources and understanding where knowledge comes from, adaptable, novel situations arise. If you can use different tools to try to get knowledge in your head. And can you frame questions on how to analyze the data? Does anybody here know what epistemology is? I had no idea what epistemology was. [Unintelligible] member of the National Academy of sciences. And he's always thinking about the epistemological basis of this, that it reminds me of many older people who are under recovery as an educator. And I didn’t know exactly what epistemology is. But it's the theory of knowledge and it's a branch of philosophy concerned with knowledge. They study the nature, origin, scope of knowledge, its justification, and the rationality of belief in various related issues. In other words, where does knowledge come from? How do we know what we know? How do we know what we know? You know, people talk about controlled experiments, but you can't do a controlled experiment for everything. How many people here think that the tides are affected by the moon? That's all correlational. [Unintelligible] having a second moon, taking the moon away, or making it so some things can't be done so how do we know what we know biomedically first is it bioplasm is there some reason to think it might be true based on what we know about bio and your physiology is there animal or model data how about observation data, these are experiments in nature, and cohort studies, natural experiments, randomized control trials, and various, like I just pointed out, it feels like astronomy, everything is observation, everything is observation. So the August-Kerb Principle by Hans Krebs, holding the Krebs Cycle, said for such a large number, there will be some animal tools or a few touch animals, which it can be most conveniently studied. So there are a part of that. And can anybody think more recently of an example of the growth principle that's anybody who breaks her? Kilo monsters reframe their digestive metabolism to accommodate changes in temperature. And they need to store, not store food, do things that they're actually thinking. And the heel monster played a key role in the discovery of the obesity drugs as a result of this. So again, an example of what the current is for action. Now, I've changed this a little bit. For such a large number of things. He's thinking about the interior, the internal balloon, and early thoughts about homeostasis, the physiological question of regulating systems. He's also the father of experimental medicine. He wrote a book, and he really lays out a philosophy of science, which is still quite appropriate or quite relevant. And what kind of study is it? X is not an event or an intervention. It's an observational event. X occurs naturally. X is exogenous. X is endogenous or self-selected. Experiment of nature, natural experiment. This would be some occupation exposure. This might be patients with an unusual genetic makeup or some unusual feature. X is an intervention to change Y. X is not randomized. It's a quasi-experiment. It's fully randomized. It's a randomized theory. So this is the kind of thing that he laid out a long, long time ago and we assimilated it as the option. And this is what we're going to talk about today, mostly. Breathing during exercise. So why did I bring that up? When I first got started in this field in the late 70s and the year 80s, there was a lot of discussion. The word drove an increase in ventilation during exercise. We had conversations about 1890 and recycles not. So at the time, the big idea was that there was something called the amplitude really championed by Carl Washington. CO2 drives from the shivering exercise, making more carbon dioxide. During heavy exercise, the skeletal muscle becomes hypoxic. It begins to make lactic acid as a result of hypoxia. The buffering of the hydrogen ion meets the non-metabolic CO2, and there's a non-linear rise in this Indiana Rogan threshold concept as I worked in in about 1977. It's a great idea. Doesn't it sound great? Carl had these wonderful drawings over here showing the mitochondria, the lungs, CO2 going out, the oxygen coming in, so forth, showing careful circulation. It was great. But unfortunately, George Brooks showed up—among other people—and put a big dent in this. One of the people that put a big dent in this was Jim Hagberg. So Jim Hagberg was working as part of the director of John Hall at his human lab at WashU in St. Louis. John had a big program in the lab. And Jim got lucky. Why did he get lucky? Because next to the human exercise lab was the Neuromuscular Research Center. And he's in the elevator and [unintelligible] they found [unintelligible] there was about 40 patients and about 10 of them studying this. They lack myofosphorylase. They can't break down hydrogen. They're essentially a human knockout. No increase in blood lactic acid with exercise. It's more than not when you're providing, you should be seen. So here you have blood lactate levels. This is the typical response in both. And this is relative workloads here. So at about 40, 50, 60% of max, their lactate starts to rise, and it's a critical rise. You see nothing in the patients with McArdle’s disease. And you can see that ventilation starts to really take off. These patients start to have their abnormal, starts to make lactate acid, and ventilation started to take off in patients with McArdle’s disease as well. And their ventilation was rising, in spite of the fact that their pH was low, which is the rest of their ventilation is supposed to go in F. so this one was one of the first major shots at a terrible threshold I did and these people are experiments of nature because there was no way to make lactic acid production zero in a regular patient through regular subjects through drugs or something you can mention so he published it in 1982 and I just imagined—and this thing stuck with me—that there would be these unusual lesions or unusual [unintelligible]. And the original studies were the big increases in deaths prior to after. Infectious disease started to go down because of sanitation, vaccination, and antibiotics. The patient for the epidemiologist needed something to do, so they started including colonic diseases, cancer and heart disease. And the other thing you've got to remember is that the people who were having heart attacks in the 1950s, the 40s, to the middle-aged men, who were breadwinners, and they were to have sudden death. And it was a huge hit to the economic well-being of their communities, of their families, of society as a whole. So it became a major, major challenge to try to understand this. And so what Jeremy Morrison's copies did is he took active and inactive civil service jobs in the UK the bus drivers people sitting driving the double-decker buses let's get over the bus to grab their ticket and they also looked at a ton of humans who were active and who were acting we showed these persistent changes differences in in coronary artery disease or evidence coronary artery disease the one being uh is that the the conductors had myangina because they were more active and more likely to get shut paid from the physical assertion because going up and down, the series was a bit of a stress test. So this is physical activity detected, yes. The effect sizes here have been remarkably stable in every cohort that has ever been studied. Every cohort that's ever been studied. It's truly incredible that you see these sorts of effect sizes. So this is, we saw an experiment of nature where this is a natural experiment. So why this topic now? Well, I was coming in Atlanta in late February 2020 at the Olympic trials and marathon and I was doing a little talk with Andy Burford and on the way back in the airport. David Epstein, the writer, tweeted this in how a boy's blood stopped an outbreak by Arturo Casoval, who was a friend of mine. So I read it, and Arturo describes a situation with measles outbreak that a boy's school near Philadelphia prior to World War II where they took plasma from people who had recovered from measles with rich in antibodies gave it to prevent other people from getting measles and this is a technique that he used many times before meeting the antibiotic in the vaccine era for all sorts of diseases. In fact, the first Nobel Prize in Physiology and Medicine was given to Bon Iberian to treat the bacteria with certain force so this idea of CAST So I thought this was sort of interesting. The idea is pretty simple. You know, a currently ill patient, they survive, take their neutralized antibodies, and you can give it for prophylaxis, early exposure, or you can give it for therapy. And this had been, again, known since about 1900. This sort of thing worked. It had been used in a flu pandemic in the 1980s. It's going to be used repeatedly beforehand. It still uses some anti-identity therapy. [Unintelligible] And every time they're in a pandemic, somebody's driving. Somebody's driving. So we started thinking about this. Arturo and I started working on it. They were going to do studies at Hopkins, outpatient studies at Mayo. And we had been in some contact with the United States. We were in concentration. We was getting a lot of interest in convalescent plasma. And when you want to use a novel compound, you can do it. Patient, which you have to get permission to and to get permission to do one patient takes about four hours. So imagine the Food and Drug Administration was getting hundreds of requests per day and they had to find the vaccine, they had to do this, they had to do that. So there was no vaccine, there was no antivirus. So how many people have ever had two-day and we were going to be 5,000 people. We did this in an effort to, one, so that we could take some pressure off the FDA, two, try to collect the data in a coherent way especially about safety. And we rolled out a website because remember the distribution we had a website we had site, MD, and patient and enrollment, we had workflows, we had navigator, we had a few tools, we had hot rod, we had the case of four tools on RedCAP, if you ever use RedCAP, yeah, we developed a real-life drop-in tool and a full -service communication tool. The first patient was transfused and over about the next four and a half months, we treated a lot of people and enrollment stopped at the end of the week. So really, in five months or whatever, here's a little bit, we had we had 2,000 sites in the state plan. That's one part of the hospitals in the United States. At 13,000 positions, we enrolled 105,000 patients as opposed to 5,000. We had to use 94,000 people. Now we get X to diversity, almost 20% African American, almost 4% Asian, and a large number of Hispanics. And this just shows where the plans go in, so it's some other things. And here are the sites we gave this at the many medical centers in the country but we gave it every zip of and gave it in rural hospitals all sorts of places somewhere in site users were going to die in rural Oklahoma in Muskova you know from the Soviet Union yeah So we did it. So what did we find? It would be great if we were doing this control trial. This is a national emergency, international emergency. So we had to do a national trial. So, and they helped us two ways. One is it became evident very, very early on that people who are immune cancer that could not make antibodies, could not cure the disease. And then when you gave them kind of less than plasma, before therapy, after therapy, they got fed. These are people with hereditary A-gamma-glotin disease, so they don't make antibodies, right? They did much better. Rare patients don't make antibodies, can have severe disease, and rapid improvement with their therapy. So that told us if we found the right patients, it's worth at least some. Now, what else we did is here's the anticoagulant antibodies. And here you can see the problem building 30-day mortality. And if you gave people high-tired plasma with full-on antibodies in it, you saw the risk of death went down. We had no idea. We had no idea how good the plasma was. We were giving people the assays for it. We just kind of made these negative apples. So this was quasI-branded. Some people got good plasma, some people not such good plasma. And you can see that among the people who are mechanical ventilators, it probably didn't help much at all. The people that were not on mechanical ventilators treated women weren't quite as sick. So again, this was a signal of efficacy. And we had this by the middle of June. And we were able to report if the Food and Drug Administration held them. And you see that there were weeks where people got body type, weeks before the rest of the So the number we found over the next is about 50% of people got a patient's time. And those weeks, 18% of hospitalized patients died. The weeks were plasma, but it wasn't so complicated before they were died. So it didn't condition this. So there's a randomized control trial to catch up with this data. And this is what our friends did and popped into it. Yeah, this is a risk of hospitalization. that you got through the treatment with just regular phytoflip fabulous so again further evidence and now back to exercising so again this is an example where we were able to use some ideas or some things I have to exercise to think about the problem so too much exercise how many people believe that you can get too much exercise and what happens to you does your risk of that go up is it you shake the curve what goes on it's sad for you but you're not really sure what it does how many people can outrun a bad diet you know I want to believe you We'll talk a little bit about blood pressure during exercise training. How many people think you can switch fiber types as fast as long? Any ideas? Yes? No? Maybe? No. We'll talk a little bit about exercise training. Is anybody here who's a barhead or what a barhead and goose is? why our bar head Dr. Chapman does anybody else here know why bar head they fly over Mount Everest and bird fight is too much exercise every time there's a wall street not only is there such a thing or maybe such a thing as too much exercise the journalists can't get enough too much exercise so but anyways how do we know what the viewers are here's a really really great cohorts that long distance can be seen this is data for 50 000 male participants 25 000 multiple races and compared to age-matched degrees. Now, that's helpful because they have a really good medical record system that are quite active. Now, this is a number of successful races. You see a dose -response period. The people who do those races have the lowest standard quality show. More finishes and faster finishes. It's also showed us for faster finishes And anyway, so this is, you don't see any kind of drift up here. So these people, I think, and who knows how they're training, but if somebody's taking a 98 cross-centric C-race cat, they're probably training a lot if he doesn't care. They did find more AFib. It's interesting, and there is probably pretty good evidence that extremely much of their life contribute to an increased risk of atrial fibrillation event. But again, not in one that anybody's come up with stuff. Here's another too much exercise. Anybody know, there's the warrants. When Boston was in 1924, a lifelong runner, he's the first math draft. D.B. Bill and folks at the Harvard Fatigue Lab have data on him throughout his life. He got cancer late in life, died in 1958. and Herman's in a guy named Paul Dudley White there's a famous cardiovascular syndrome called Will Parkinson-White syndrome which is Paul Dudley White and White was one of the kind of rude advocates of what we would talk hard to hear so if Mark dies and something happens according to Paul Thomas Paul Dudley White essentially turns into a bit of a brainwave and these were the four modern ideas about informed consent Well, let's just say somebody did an autopsy with a heart. That'll hold up, of course, a heart. Well, what did they find? They found that he had plenty of plaque, but he had huge, huge, huge, huge, huge, huge, and that's been shown over and over and over again, that lifelong endurance exercise training makes people's coronary arteries big. There's a lot of discussion today about coronary calcine and people that are lifelong exercises, but, again, there's really good evidence from a variety of studies that have much greater coronary arteries. So again, two merits in natural experiments. Now, you can't outrun a bad diet. For Tour de France participants, the only labeled water, they ate 5,000 to 6,000 calories a day and only lost 1.5 kilograms in three weeks. And this is long before modern ideas about feeding people gels, and all sorts of other things. So again, not so much. so these people can really really and this is a really interesting conversation now because as postulated that humans can only eat about 2.5 times their vasometabolic rate over prolonged periods of time and there's kind of an upper limit of energy expenditure over the course of a year so this is a short time period this is a friend rise of this is a well known he's a professor there and a charity ride to the France course to raise money for him he ate huge amounts of food and no weight gain and a colleague from Spain had data from the pros so if you look at Chris, Chris didn't lose any weight he ate about 8,500 calories per day 5,500 calories per day. The pro about 7,100 calories per day. The duration was 87 hours versus 191 hours, 3.45 watts kilo versus 1.5 watts. So again, just an idea that people can, for three periods have these extremely high floor intakes and expenditures. There's been some data on triathletes. They're training over the course of the year that I've seen, and they go weeks up to 2.5 times your mesometabolic rate, but they occasionally take an easy week and they occasionally do this and they occasionally do that. If you take all 52 weeks, they're probably right at 2.5, maybe 2.7. But again, you're not going to be able to study this. You're going to only be able to find some of these issues. Now, here's my favorite one. In one of the least appreciated papers of our partners, this is from warriors in the division. And they found in the National Warmer Studies, they didn't include the version of French-sized presentation. The active twins in 68 per week didn't do much. And look at this, sedentary twins had BMI's ranging from 19 to 33 to 36. The active twins were between about 19 and 26 or 27 and nobody got into the obese category so you know how genetic is it maybe these people could have when the bad guy or their genetics there's later data by William many more pairs of divergent twins so you would expect identical twins that would be 0.8. But showing that with the couple of accelerometers per day that they ran, you started shifting that way. So our genes are necessary to guess. And here's my summary. This is from the great book by John Carter. Once along there, he turns this up and he didn't even worry about big minutes. I have a 15-year-old swimmer and he shows it every day. blood pressure regulation during the next time huge controversies again since the 1870s or 1880s about whether it's or cellular muscle send signals to the heart and the brain to make blood pressure go up and it's a huge controversy and it's still a very active area of what these are what do they do how is it found this is from Alan Spurt study conducted in a colonial region. He'd been trained in London, but you wouldn't want to have a job to study. You need to send him to Cairo first, right? And so it does feedback from muscle regulate blood pressure and exercise. And a sustained increase in blood pressure post-exercise shows signals from most of the this is a control This individual starts to exercise, leg blood flow collusion happens here, and then the person stops exercising, blood pressure stays elevated, and it goes down. That's classic post-exercise ischemia, which shows a sustained increase in blood pressure. But they found a guy in Cairo who had an insensitive leg, had a partial spinal cord injury, so the motor system didn't want, but the leg was insensitive. And what happened when they did it in the intensive life, blood pressure still went up, but individuals stopped being sure that the blood pressure went down. There's two interesting things here. What is the blood pressure down? Sensory curves didn't exist or injured or boobs. That means the blood pressure was pretty similar. Well, this certainly shows that the nerve reduced something, but it probably shows that there's some overlap between other signals. Again, this paradigm is the it's actually been additional studies, patients that they don't have this rise in blood pressure, because of the so somebody is having this since drop in blood pressure. So one subject changes our understanding, one subject changes are understanding, and leads to an experimental impairment still in the use today. Now, another big thing that's happened is what happened to blood pressure. The idea that was very prominent, again, in the 80s, 30s, and 90s, that the ability of skeletal muscle to vasodilate could outstrip, could outstrip cardiac output to humans. And if the muscle dilated too much, he would never fall in the blood pressure. so my teacher John Shepard along with Bert Marshall and Alex Schurter found six people and he had a very little more sympathetic now why would you cut anybody's sympathetic and this is from I think 1961 so why would they be cutting anybody's sympathetic purposes does anybody have an idea how do you think they treated high blood pressure in the late 1950s there were no drugs there were no drugs But how many people would be alarmed if they saw, you know, the person in the exercise program had blood pressure from 60 over 20? Everybody would be alarmed, right? These people, before they were treated, had blood pressures of 250 over 150, some 300. So people used to come in with this incredibly malignant hypertension. They would have strokes, brain bleeds, and they're literally going blind. And the question is, what to do with them? So the surgeons are never wanting to miss the opportunity to operate. We'll just start cutting their sympathetic nervous systems out. So they cut sympathetic nervous systems and they work. Look what happened. This is the extracted exercise response. Look what happened to these people. They had no sympathetic nervous system, regulate the blood flow of their cracking muscle. So really, and we did this even when patients were head down to make sure they had [unintelligible] to continue to have. And these really anticipate ideas from the 1990s about muscle dilator, absolutely a few threads. So again, things that we, and I spent a lot of time in the 1990s and early 2000s, things that were anticipated in the 1950s and 60s, based on the pain for SMIRC, I should have told you about SMIRC in the previous slide, and the study de Piro, SMIRC went back to New Zealand and started to treat blood pressure with drugs. It was one of the first people to treat blood pressure with drugs, so they didn't have to be used to come up with drugs. How about the limits of added building training? Another training said that the European Journal applied to the WNB on the sedentary training for 30 years. Here we have the expected differences in GFQ Max 35 versus 15 differences in body composition. Look at this. This is the type 1 blastocyte, almost 100% in the active group, and only about 65% in the end of it. So if you look at the training studies, it's been up to the time there, 12 weeks, 20 weeks, whatever, and you see some evidence of a shift, a little bit here, a little bit there, but this sort of transformation can only have been seen lifelong training. Only seen lifelong training. Again, so this is another advantage of past to get a much bigger dose and duration of intervention than you can during an experiment training and aging exercise I get more and more interesting and does anybody know why the University of Indiana is important to that data. All right, so this is from Greg Heath working in John Alley's. These were master athletes who trained hard. Several had been lifelong athletes and the VO2 max starts higher, 5% per year versus 10% per year. The evidence was that the stroke volume can be high compared to the data still. So this is kind of a theoretical basis of the idea that aging instead of being 10% per deck date, normally active people can be as low as 5% per deck. So why is the University of Indiana important out here? Any ideas? Somebody knows? Who's the first person to break 90 minutes for two miles? Don Lash, where did he do it? Correct. What else is interesting about that? There's VO2max data from him in the 1930s. He's ministered. Minister, Lash had a VO2 and he had a new resident. He published it in Science called New Records of Human Power. They had a VO2max and they knew a lot of things. And they had VO2max on his front. 75% and lashes so yeah lashes out here's the place and the train is but again another small experiment not the first part but the second part this is from the classic Dallas Federal study in the middle of 1960 five well I've helped me in college two athletes, three sedentary individuals put at bed rest for three weeks. Why would you put anybody at bed rest for exactly three weeks in 1966? Who would find such a Yeah, because the problem was people were faced by some who were under tremendous condition, come back after three or four or six or eight days in space and just be completely blazed out. And wanted to know about D-conditioning. So here's what they showed. Jerry Mitchell makes some tea, and Jim Longfrey showed that he had his big D-packs. And Ben Levine, my big friend and colleague, we found these things 30 years later. And it showed, and they found them 40 years later, I think they found them 50. And it showed that 30 years, three weeks of bed rest was equal to about 30 years of D-drain, for 30 years of aging. It was just a remarkable point. It's really a great study. Again, a natural experiment or an experiment to be sure. This is Exercise Capacity Training and Aging. This is, as you get older, this is Frank Rutherford, a short -letter to the JAP in 89. And these are Sid Robinson, who I worked here for a long time, Bruce Dill and Sid Robinson, come from Harvard Fatigue Lab and a man named Bernie Vanthamson who worked at the Arkskrogate Institute maybe not the Arkskrogate worked healthy invented their DO2 max with DG and the interesting thing is that Dr. still had his DO2 max transferred into the sleep and I was involved in one of the middle and he had an ACS in the reason he said he thought about when it's VF2 Max where he told ways on the bottom three for getting this but anyway, one of the things that Frankie did is this observation available and Dr. Hill also mentioned he thought that maybe if people get older patients VF2 Max it became an issue of skeletal muscle mass and sarcopenia And Dr. Dillipolis, he gave a lecture a few times. Again, in the middle of the 1980s, he was born in 1890. He said the thing that he noticed that was about into his 80s was just this progressive law of the muscle. All right. Now, let's get into the human development of the body. And how many people think that a right shift, or any hypothesis, the right shift of the oxygen hemoglobin dissociation curve, but the hypoxia is a human thing. Because it allows you to unload more oxygen from the hemoglobin and get that oxygen to the hypoxia tissue. So this is a conventional wisdom. This is like what they teach in the second paper. See the first thing. All right? And it's a massive thing. So you can charge it. So this is 50 % hemoglobin associated with oxygen. had a po2 27 and you can see a right shift that was that always bothered because they fly from out there instead of the air going in and out it goes that way so that uh there's almost no difference between environmental oxygen and oxygen are purely pure system so at sea level the pf2 150 and the arterial between in humans or mammals birds it can be 150 150. When they get really high like ever since the 30s. It's really, really fun. They have left-shifted food, saturation, very low PO2. They have all sorts of things that are loaded and 50. Red blood cells and lots of but the standard of teaching is that a right-shifted is such a meditation because not only are bar-headed geese left-shifted and llamas are left-shifted. there are things called deer mice that are around in Nebraska and in Milwaukee, and as you look at the deer mice in the plains of Nebraska, the deer mice that they find out the place being defined, genetic selection for left -shifted hemoglobin, all sorts of stuff. So what did we do about it? We found a family of people with something called hemoglobin palpins. Just humans that have left-shifted hemoglobin, there's all sorts of variants. We hear about simple cell disease, pathologic forms of hemoglobin, hemoglobin oprogies. There's all sorts of hemoglobin variants that don't really come full of. So these people had left-shifted family, they had 16 instead of 27, and they had minimal reduction in their VATMX at 15%. This is what we saw in controls of left-shift. So as I reflect on that, one is knowledge, again, and again, the tools we have to gain knowledge are tools and not knowledge per se. There's nothing special about the way I'm going to go. There's nothing special about the way I'm going to go. It all helps us get more to generate insight. But again, knowing where it's not as focused on, what tools we have makes you adapt to situations for instance, in analyzed data. And this is something people learn around this list of patients. This is a case report. A case report is in American from the proceedings of a period of disease that mental health. So this is a patient that had COVID. Now this patient had COVID 270 days. At the time it was just a notice that a patient had breakthrough infection. Turned out that the amount of antibodies in the blood of people that survived a breakthrough infection after that extension was 10 or maybe 100 or even 1,000-fold higher than the plasma we had earlier in the pandemic. So, you know, I committed some good friends at Blood Bay to collect some of this and we gave it to the center. This is what happened in three days. And it's over and over and over. I wonder about, so we treated, like, some of the people that made it with this, large numbers of people treated all over the world with fast plasma, which I just thought it was a favorite of individual patient analysis. And so would this have been tried if I had not learned about my cargo patients? I was in my mind before my I was very lucky to be exposed to a general major and I think it helped me and again that the uh but someone uh zach and rob at breakfast this is almost uh last year but we had uh we have a fully approved deputy we got it across the finish line uh it was a partnership between the academic community government and not-for-profits no harm so how many people get a drug, you know, that's pretty good. Our good friends, that's really on the side. Apparently, Novo's building some facility down here, too. So, good. You got that across the finish. And then I think about what else? What else you can learn? This is something that was just ocean or tent. There are families, you know, so the effort to find a cure or a treatment for all people could vary, very, very small. The drugs that are out there are marginally affected. And people have been focused on Philip, Van Wood, and the brain. But here's an interesting story about it. A 76-year-old male came from family, where everybody in the family, the extended family has a cognitive impairment, and if they carry a specific gene by about age 50, he made it to 76 cognitive. He was positive for the gene. So, why is he protected well understanding why is he protected so we hear a lot about big data we hear a lot about AI we hear a lot about modeling but sometimes perhaps big breakthroughs may come if we understand things about patients like this and what insights they offer why they're resistant to disease or more susceptible I'll get started. Great talk. Thanks, Mike. So I thought you'd nicely range all the different types of habits. And then you said, Mark, the job is to put them together as a puzzle. Right. But how do you weight the pieces differently based on where the evidence comes from. Well, you know, some people have been interviewed with their intervention with RCTs and the evidence of RCTs, or even better yet, I have a synthesis of several RCTs. I think that that is generally appropriate, but not always appropriate, and you have to recognize that some things you can't do an RCT on. I think you also have to think about what effect sizes you're looking at. Rob and I were talking about it for the presentation, and in human performance in sports, the margins are tiny. Margins are tiny. And so, you know, what people are looking for at altitude training is very different than what they're looking for at outcomes like the obesity drugs. So I think you have to kind of, and I think that's where some judgment and experience comes in. So that's kind of a non-answer, Zach. So, you know, trust me, right? Yeah. Yeah, right. But I think more importantly, you have to say what are the strengths and weaknesses of the data that you have. And also you have to think, you know, what is the, at least when you're thinking therapeutically, what's the implication of doing nothing? We showed very early that without an RCT, the plasma was safe. We showed that within a month, the first 5,000 patients. So once we know it was safe and it was biopausible, it might work, why not? Why not? You know, in a desperate disease with no known treatments versus, you know, if it was something that could kill people very quickly. If it was a chronic disease, you know, you might have done something else different. So you have to bring it in that context as well. Yes. I think that's important for everyone, but particularly like the students in that the goal is building up the knowledge base for being born to make these types of diseases as opposed to a cookie cutter. Right. And the policymakers and people, you know, who's going to pay in the U.S.? You know, who's going to pay for things, what policies you're going to make, so on and so forth. And to be involved in, it's interesting because, you know, I've been involved in a couple things recently that have policy implications and to watch people, you know, weigh the science. I mean, and people weigh things other than the scientific evidence. I was working in the clinic during COVID and actually spent weeks in, up to Ryby. To get the labs. Oh, good. I'm just wondering. What kind of patients were there? We were, like, chronically ill. We only had some kind of genetic thing. How young were you able to get the IRB? The individual IMDs continue to give for children to very low young levels. And I think as long as you had evidence that people weren't making antibodies or won't make it, I'm not making sense to do it, because this is essentially fresh frozen platinum, which is a blood product that is used hundreds of thousands of times per year, and it's quite safe. So once you establish your own new arm, I think it's I just don't know how they are about Yeah, right. And again, you know, what that, you know, issues of regulation, IRBs and so forth during the crisis is a separate issue. Iman, like, you know, we had two -day IRB approval. Well, when the pandemic hits AMPA, there's a lot of people that only speak Haitian Creole. so how do we get how do you get that patient real well normally you know you have to go get a translator so it takes six weeks at least we crowdsourced it overnight and because of what was going on people said fine you know close enough you know the enemy of good is better I think and I've written this thing up and whether it's disaster medicine or disaster or any type, how people need to approach that versus normal kind of bureaucratic administrative thinking. And the last, I have about seven rules, but the last one is the enemy of good is better. And you've heard that. You're an RN? Right. Yeah, right. Okay. So, yeah, so you've heard, you certainly know that, you know, from your son of a course, sometimes the enemy of good is better. Other questions? um changing focus a little bit four minute mile forward yeah right um that happened anytime soon you know that's interview robin and I were talking about that at breakfast the uh we you know that that's been postulated and so forth this whole in shoes pacing certainly basically you know we can try to uh this summer anything depending on uh how accurately Nike chose or not chose the time and she may or may not have gone a tenth or two of a second faster. Certainly there are women with the aerobic capacity who run very fast, we have two max in the 70s. But the big problem is sort of anaerobic power that's required. You know, I know 10 or 20 people who've drunk in four minutes, and they can all run 400 under 50 seconds. And I would be, and the people that can go really fast, they typically can run 46 or 47. so I think that and what there's about 10 women in the history of the world or 20 women in the history of the world that have broken 49 seconds so I think the big issue is going to be this sort of and road yes seven seconds away right and the efforts to pace into the other things that they've done in the two hour marathon didn't seem to make as big a difference It's not whether they can do it more optimally. And remember, you know, it's unclear, you know, if any undoped woman has ever broken 154, 155 for half, right, Ron? Well, you're also assuming undoped, but I think we can assume. Yeah, let's say people that have passed drug tests, people that have passed modern drug tests, and they've gotten a bit so 154, 155 and again, all these individuals who can break 4 minutes can run 1.48 or 1.49 so yeah, so I think it's kind of been yes ma'am this work showed that there was a ceiling in how much people have in terms of energy expenditure seeded that ceiling and I was wondering, is it that you can eat that allows you to break through to the higher amount of so-humming. From any sorts of brief periods where people can be way over it, they eat a lot of carbohydrates and fat. And if you read about the guy who just hit all the 14,000 foot mountains out west, I'm blocking his name, and rode his bike between mountains and so forth and so and the guy was guzzling olive oil. Yeah, Iman, literally, he was supplementing his diet with olive oil, you know, to get the nine calories per ml. Yeah, so people do pretty extreme. So they didn't lose weight, but, you know, I'm not sure I'm really starting olive oil, putting a coffee, I guess. Yeah, so people are willing to do pretty extreme things. Yes. So I'm not in kinesiology. I'm a biostatistician. thoughts you know to say this right away so I’m very happy what you said about data data is not not data are not there this is you know it's like more days that doesn't mean more noise so the question that I have is about the Swedish time that you're sure yeah cross -country right yeah do so much should be associated with better health right right right yes selection up front exactly have a healthier cohort to begin with and that's been one of the arguments is professional baseball players live a long time you know and and they're not particularly fit by other markers but you did you select for big strong people who just are more resilient to begin with so that's always the confound here they dealt with that a little bit in the bus driving bus conductor thing because they had similar these were civil servants so taken off the street so probably a less selection bias to begin with, and they had similar uniform sizes when they entered the bus ride, the transportation service. But again, that's always the problem with these natural experiments. How do you make fair comparisons of the cohorts? Always, always a problem. Other questions? Awesome. Do you have any thoughts on the occupational physical activity paradox? Yeah. These data that you showed from Jeremy Morris, like you match for occupation to other physical activity, but like now it seems that people who work jobs that require more physical activity do worse. They seem to be protected. Yes. Yeah, or do worse. I think because the remaining people doing jobs that require a lot of physical activity, I think that those jobs have gotten increasingly, you know, more owners, and I think that you are selecting for individuals, not selecting, the people that are continuing to do those jobs are individuals with relatively low agency. and so it's you know the kinds of people that used to be mailmen when I was a kid are very different than the kind of people you know walking around delivering the mail loss compared to people that are you know digging ditches today so I think that's just how much control people at Locust Control all that stuff so Ideally buy that a lot yeah and people that are doing a lot of mail they pronounce tough work and they've got talk about founders they've got typically a whole bunch of other socioeconomic things going on where those bus drivers and bus conductors would have been comfortable middle class civil servants at the time yeah yeah and that's one and the extent to which those jobs disappeared is a real problem yeah real problem other questions yes So, with the brand-minded control, what's always bothering me is a lot of them to treat you as if we can do so to that, especially when we speak to you. Yeah, oh, yeah, right. Right. So, but the problem is, we'll see if we can't do it, and we'll see if we can't do it, and Well, I think we have to always remind people that there's no RCT showing you that smoking is bad for you. You know, so we've got to start with sort of first principles. There's some things you just can't do in RCT and these behavioral things. And the duration of the intervention, the dose of the intervention, you know, Iman, In Dan and Dr. Holot's lab, the late Bob Hickson did a study where he subjected six or eight kind of generic hospital workers to just extremely hardcore interval training, three days a week, followed by hard, what we call threshold training, three days a week, right? And their VO2 maxes went up about 30% in 10 weeks when they started to train like professional athletes. A number of people got their VO2 maxes from the 40s into the 60s. and how many people wanted to continue to train none because they offered to continue the study and you got you got to think about the subject burden and so forth so yeah I think it's a big problem and I think that that the you know the at least in clinical research the rct people of if and I know having worked uh worked with the government during there's there's some very sophisticated statisticians at the FDA were thinking about this. And they're also talking about, you know, approving things on the basis of less than perfect data and then figuring out how the data emerges. But the flip side is not the same. Sometimes you'll see signals in an RCT that are quite favorable. And then they look and they're like, there's been a couple of cancer drugs approved that showed that, you know, the extended life, but they were done in younger subjects, kind of healthier subjects. And when you go look in the insurance databases, there's no evidence they work some liver cancer drugs in particular so yeah so I think it's again you have to take a holistic view about how you're looking at all the data question oh you're going awesome so from the makes sense or is there any data on things like functional tests the equality minimal and see it because And that's exactly, so Dr. Robinson, it's a great question, because that's exactly right. So we had to get an outcome that was yes or no. They died, they didn't die. For a while, ICU admission was yes or no. But as the pandemic progressed, who got into the ICU, the criteria for who got in the ICU changed. So on these real -world studies, it's important to have, you know, a non-debatable endpoint. Because if you have a debate at one point, somebody will debate about it, right? But, and the other thing we have, our statistician friend made a comment is and Blair knows a lot. I've been lucky to have a real savant finding Ricky Carter be my statistic partner in all of this. And he's put a whole team together with a lot of younger people in age groups. Some of the folks in here who made the flight. and um anyways and so you know um and I asked Ricky questions and blow the ideas to him but he claimed stupidest thing he ever did was teach me how to do a square desk so I think it's important to recognize whether you're a consumer of statistics and get a get a real person that can help you so we were able to design and study as fast as we were going with a bunch of prospective stuff embedded in there that allowed us to probably reduce the total level of stupidity to some extent. Yeah, but the key thing is talk to your good friends and statisticians, and God may hate it too when you bring them the data afterwards, so you can talk to them sooner rather than later. They're right to be mad at you. That's a good ending note there. All right. Yeah, we give the statisticians permission. Absolutely. Well, thank you very much. We have a little gift for you here in terms of added to your collection probably with this CV that we heard about. And that little inscription there, and I believe this would be, let's see, light and truth. Light and truth in terms of our inscription was selected by Robert and second by Blair. So that's an awesome situation. Is that like the model of the university or something? It is. It is. Thank you. Let's get to it. I like that. Blair, there you go. Thank you very much.

Description of the video:

Okay, good morning, everyone. It's 11 a.m., so we're going to get started. So it's my pleasure to introduce our speaker, our distinguished colloquium speaker, Dr. Joe Brown. He earned his PhD in Environmental Sciences and Engineering at the University of North Carolina Chapel Hill Gillings School of Public Health, Global Public Health, following graduate training at the University of Cambridge and undergraduate studies in civil and environmental engineering at the University of Alabama. Dr. Brown has held faculty appointments at the Georgia Institute of Technology and the London School of Hygiene and Tropical Medicine and now he serves as a professor of environmental sciences and engineering as the director of engineering programs and director of the UNC Water Institute at UNC Gillings. Over more than two decades Dr. Brown has built enduring collaborations with communities, researchers, and institutions in the U.S. and internationally, with extensive work in Cambodia, Bolivia, Mozambique, and many other settings. His research advances sustainable drinking water treatment technologies, novel sanitation and infrastructure approaches, scalable water quality testing methods, and rigorous health impact trials that strengthen the case for public investment in environmental health infrastructure. Dr. Brown is a nationally recognized leader and award-winning scholar, including being the recipient of an NSF Career Award, and he is deeply committed to educating and mentoring students at the intersection of engineering and public health. One of his former trainees is now a professor in our department, Dr. Capone. Outside of the lab, I learned last night at dinner that he's also a bad informer. Dr. Brown, we're very excited to have you and learn more about your work today and particularly about the topic that you chose to talk to us. So please join me in welcoming Dr. Joe Brown. Thank you so much for the kind introduction. Can everybody hear me out there? I'm going to make sure that all of this is working. Let's see. Can people online hear me? I think there are a couple of people. I'm good. Okay. Well, thanks again. Thanks again for the introduction and thanks for welcoming me. Thanks for the invitation to come speak with you today. This is a great pleasure for me to be here. I've never been to Indiana before. I've never been to the Midwest before. I have been to the United States before. I just haven't been to like this part of it. And I look forward to getting to know it a little bit better. It's a beautiful, beautiful place. And congratulations on your recent national title in football. I'm from Alabama, so we know something about that. And anyway, it's nice to be here. So I forgot the name of the actual presentation that I had submitted. Somebody asked me for a title. It wasn't this one. But as I was thinking about it and thinking about all the things that I'm concerned about in the world, I thought, yeah, airborne feces, just one more thing to worry about. So I'm going to talk to you about bioaerosols and the transmission of enteric pathogens through the air, which is a very understudied but potentially really important and interesting topic. Okay. Okay, so I'll start out and just say a few words about what I study. So my research group studies environmental health microbiology. I was trained as an engineer, and mainly I study public health. And sort of the intersection is really microbes. I'm really interested in microbes. So I'm interested in water, wastewater, increasingly do a lot of work on bioaerosols. I study microbes whenever and wherever they are. If they're in the food, if they're in the water, if they're in the soil, we're looking at them. I do a lot of work on monitoring methods and surveillance methods for pathogens, especially fecal indicators and antimicrobial resistance. So I'm very interested in innovating on the methods that we use to monitor these things. And the reason is it's very costly and logistically burdensome to take samples in the environment and process them for pathogens. So I'm always jealous of our air pollution colleagues who can generate 10,000 data points per hour for whatever they're measuring. And I feel like I really want to go in that direction a little bit, but it's very hard to measure microbes in the environment. I've done a lot with using waste streams for surveillance. So you may have heard about wastewater-based surveillance. surveillance. I'm sure there's a lot of work here also on environmental surveillance. So I do work on that. Very interested in improving exposure assessment. So understanding not just when and where microbes are in the environment, but how they come into contact with people and what the health implications are. Very interested in technologies to reduce exposures. That means both infrastructure, making infrastructure work better, but also treatment technologies. And we do a lot with estimating health impacts of water and sanitation technologies and infrastructure, which is really the sort of link to global environmental health and policy. Like, how do we find out what works to reduce the burden of disease associated with poor water and sanitation? And what is the investment case in public health terms for investing in technology? So, and I work, I would say I've worked in about 25 countries. I've worked, I've been into more countries than I've been to states in the union. Obviously, I'm adding check checking Indiana off the list today. But I work about half of my work is international or half is international, about half is domestic. My domestic work is mainly in in Alabama and North Carolina and in Virginia. But also have longstanding collaborations and studies in Bolivia, Cambodia, India, Zambia and Mozambique. so when I just to introduce the topic of microbes flying through the air you may know from the history of public health that that cholera was once thought to be a miasmatic transmission of disease right so airborne airborne transmission of cholera this is a cartoon from the 19th century showing cholera wreaking havoc across the armies of Europe. And if you looked at the, well, let me just say that the major transmission pathway that was under investigation at that time was airborne transmission, and there were some very interesting reasons why people thought that airborne transmission was happening for cholera specifically. So this is a cholera map of London from 1849, And the dark colors are places where you see lots and lots of cholera cases. And there were some very clever early statisticians of public health, including William Farr, who published these data, which showed a very, very close correlation between cholera mortality per 10,000 persons and elevation in feet above the Thames River. Right. And it looked like there was a very good correlation, like the closer you were to the Thames River in terms of elevation and therefore with the way air drainages work, potentially your exposure to air that emerged from kind of the river bottom, it looked like there was a very clear correlation between cholera deaths and elevation. So this was used as rather convincing data to make the case that cholera is being transmitted through the air. This is another graph of those same data showing the correlation between elevation and mortality with cholera. And lots of maps were produced, right? This is before the germ theory of disease was universally accepted. And this is before cholera as an organism was actually microscopically identified. It wouldn't be identified until about 13 years after this graph was made. Right. So but then, you know, the rest of the story, right? Jon Snow came along. This is Jon Snow had a great, great, you know, figure in the history of public health. And you will have seen this. Right. Everybody knows what this is. Right. This is Jon Snow's cholera mortality map of central London, implicating the Broad Street pump, which is right here. if you can see my cursor, right? And these little black bars are deaths associated with cholera that are all clustered in this area. And there were some interesting things about this study that really provided the evidence that that pump was implicated. One was that there was a brewery right here where nobody got sick because they were all drinking beer. There were also clusters of cases in other parts of London that had some connection to the water at the Broad Street pump, like there were some families that had moved away that they still gathered water from this place. And this, at a stroke, created both environmental engineering or sanitary engineering, as it was once known, as well as epidemiology and, I mean, GIS. There's a lot of confluence here in our disciplines. And this really became the central moment when we started thinking about drinking water primarily as a public health amenity that would benefit cities broadly, right? It was in the control of cholera. Several years later, the cholera bacterium was discovered. And with all of this science, with this sort of new knowledge that water was implicated in the transmission of cholera, the miasmatic transmission of disease fell into disfavor. But it never quite went away because lots of other studies showed that air actually could play a role in the transmission of disease, including of diarrheal diseases and other kinds of enteric disease. Fast forward 50 years to the early 20th century. So in the early 20th century, there was a newfound interest, even as all of the water and sanitation aspects of enteric disease were running like a 19th century locomotive down the track. Other folks were still interested in interrogating the potential for air to play a role in disease transmission. This paper from 1907 studied bacteria that were known to be fecally associated and their migration elsewhere in systems. Like, for example, here, it was shown in this study that bacteria from sewage was detected 73 feet above a point of discharge that was subsequent to splashing in a sewage system. So there was some mechanism for aerosolization, and then it was measured at a great distance. Fast forward again, another 70 years, and we see with the advent of wastewater treatment here in the United States and in other wealthy countries, the process of secondary treatment of wastewater, which involves aerosolization, which can result in aerosolization of fecal microbes. and there were a whole raft of studies that the EPA commissioned to look at this question of whether implementing centralized wastewater treatment could relate to the migration of fecal microbes and potentially pathogens from this new infrastructure. Mostly those studies showed that while pathogens can and do emerge from wastewater treatment plants, mostly they are inactivated relatively quickly and don't really pose much of a risk to communities beyond wastewater treatment plants. But the possibility was never 100% discounted. I mean, this is something that has been observed. Other studies in the 1970s showed things like, I love this one. This is a study that looked at the migration of fecal microbes in a toilet bowl as a result of flushing. So this is a classic study led by Chuck Gerba and Joe Melnick, wherein they seeded microbes, including viruses, into toilet bowls and then flushed them. And one of the things they did was they would put filter paper on the top of the toilet lid, close it, flush it, and the fecal microbes would come and make a characteristic pattern on the filter paper, which they called comodograms, which I thought was great. But you see very much like whenever you flush a toilet, the microbes that are in the bowl, they form a plume and they go out into the room and settle around. This is not a controversial notion. So there was a lot of historical antecedent to this. And I would say just like where this science has been up until the last 20 years is that wherever you have concentrated waste and mechanisms for aerosolization, you're going to see bioaerosols. So that includes wastewater treatment, as we've seen, also land application of biosolids. So enteric microbes in aerosols have been related to that. They've been related to urban surface waters. There have been studies of concentrated animal feedlot operations. Like if you go in and around the big hog farms and chicken farms that I'm sure you have here in Indiana, you will be able to find fecal microbes that are present in aerosols. They've been identified in relation to toilet flushing, as we've just seen, as well as water features, pavement cleaning at the beach through wind wave and wind shore interactions. There've been some really interesting studies recently near San Diego. Did anybody see those studies. There was a great paper published in Science about the migration of specifically H2S from sewage in Tijuana that was causing an air pollution problem across the border in the US that was really interesting. But that was also accompanied by microbes. And also, when we study bioaerosols in indoor environments, especially in high-risk environments like hospitals and daycares and nursing facilities, we do tend to see enteric microbes present in bioaerosols. So they are there. And you come across really interesting studies like this. Like this was a study of airborne microbes in the Louvre over time. Has anybody been to the Louvre. Yeah, so the Mona Lisa is there, right? And if you measure aerosols inside the Louvre, where the Mona Lisa is, it's about, you can find about a thousand E. coli per meter cubed of air, and it's remarkably stable over time. And why is this? You have lots of people coming in and out of the building, there's lots of toilets being flushed. So there's, yeah, if you sample the air inside buildings where there are lots of people, you will find fecal microbes flying around. Relevant to the Midwest, there was a great study of urban aerosols in Midwestern cities a few years ago that identified dog feces as the dominant source of aerosolized bacteria in the winter months, especially in Cleveland, Detroit, and to a lesser extent, Chicago. So that's from sequencing data where we've taken aerosols, sequenced them, looked at the microbial composition and determined through source tracking and other means that, you know, animal waste makes its way into the air. Does this make anybody not want to breathe, by the way? Yeah, I don't know. I mean, the majority of my work and everybody else who works on enteric pathogens is still through water and wastewater. water. Those are likely to be the dominant transmission pathways. We're interested in microbes on surfaces. We're interested in those microbes in food. But it turns out whenever you actually start to look for it, you do find it in these places. So those are the questions. So just to summarize the trends over time, you know, we started out with theories of miasma, bad air, and we thought that probably causes many diseases. But through the early studies of cholera and later typhoid fever, you know, we found out, especially through, you know, some early pioneering work of microbiologists that miasma actually is not a thing, doesn't cause diseases, but germs do. There have been a lot of studies for at least 100 years of the transport of airborne bacteria, including enteric bacteria, often at low concentrations. But we do know that some airborne transmission of disease happens, like obviously respiratory pathogens, measles, TB, some influenza, and possibly COVID as well. We know that enteric microbes are documented routinely in aerosols. We know from the studies in wealthy countries that the risk of transmission of pathogens and the health implications are probably low for modern wastewater infrastructure. But most of this evidence has been from culture assays of bacteria that don't really persist in aerosols for very long, like E. coli is very unstable in aerosols. It tends to be inactivated very quickly. Or we have molecular detection of fecal indicators that are everywhere we look. all of the studies that we've done of wastewater infrastructure or waste sites have been in wealthy countries rich places where the burden of disease is pretty low and um studies in low in i'm sorry and most of them have been in low burden settings where pathogens are pretty are pretty rare so all of that like looking at that science looking at that more than a century of science kind of led me into this question of what if we looked for bioaerosols associated with some of these enteric pathogens in places where wastewater is not very well contained, where it's not treated very well, where the pathogen burden is really high, and where the other environmental factors might exist that would contribute to their persistence in aerosols. So I do a lot of work in low and middle income countries. This is a place where Drew and I both work in Mozambique, where we've studied bioaerosols. A lot of cities in low and middle income countries have open sewers or other places where wastewater is not very well contained and that are in very close proximity to places where lots of people live. This is a river that is basically the major wastewater canal for the city of La Paz, Bolivia. This is called the Rio Chacuyapu. And it's where all the wastewater from the whole city goes and goes right through the middle of town. So all of the industrial waste, commercial waste, residential waste, and also all the runoff go into this river. So it's like basically 100% wastewater. And you can see that it has engineered cascades in it. These are for a couple of reasons. One is because the elevation change through the city is so dramatic that there's lots of opportunities for little waterfalls. But also when they've channelized this stream, they built those in as well as a kind of treatment, right, to kind of entrain water into the wastewater. But you can imagine how if you're interested in bioaerosols, like this is a pretty interesting place to be, right? Because you've got these mechanical mechanisms for the generation of aerosols, as well as a very high concentration of pathogens that are present there. So obviously, I send my students there to like stand over it and have a look. These are wastewater canals, open sewers, if you like, in Kanpur, India. You know, also there's all kinds of, you know, there's wind that blows across this. There's splashing of water that comes into these types of canals. There's a pig swimming over here in the wastewater canal. Yeah. So just looking at and knowing sites like this and also knowing the sites and knowing the science around, you know, where some of the gaps are in our understanding of bioaerosols led me into start asking questions. So, you know, about 10 years ago, I started with just piloting, going near to these sites and taking aerosol samples, right? This is an aerosol sampler right here. It's called a bobcat, which sucks 200 liters of air per minute through it and captures microbes on a filter, which then we can elute and measure. These are, this is another team of people over here. We're capturing some aerosol samples. And we found in our initial sampling that 80% of the air samples near the Chakiapu were positive for culturable E. coli. So when we started collecting them, we found pretty high concentrations. This is actually lower than in the Louvre, if you remember that. But still, we found a lot. This particular method of capturing aerosols is not great about preserving the viability and culturability of bacteria. And so this is probably a very, very, very low-end estimate. We also identified by molecular methods ETEC or Entera Toxigenic E. coli, Shigella and Giardia near open sewers. And this is, to my knowledge, the very first identification of Giardia in an aerosol sample that's ever been reported. Yeah, this is me hard at work doing some research. This is the Ganges River over here in India, which has many properties, but it also receives a lot of waste and wastewater. So it's pretty polluted. What you can't see in this picture is the whole band of rhesus macaque monkeys that are present just over here. And they are trying to steal my sampling equipment. I don't recommend trying to sample around troops of rhesus macaques. They are trouble. Um, so I spent a number of years traveling the world and, um, and also my students, uh, traveling the world to collect aerosol samples in and around interesting places where I thought maybe we'd find some interesting stuff. I also studied things like, uh, mechanical, uh, pit emptying of latrines. So this is when you stick a big hose down into a latrine pit and suck the contents out for disposal. That's a mechanical process that agitates all of the fecal waste that's down in there. And we published a kind of an interesting paper that looked at the spikes in microbes that you would see near places where desledging is happening, including pretty high concentrations of E. coli. And we identified a bunch of pathogens there as well. So the question I was left with after doing a lot of kind of pilot work and thinking about this is, you know, which pathogens are likely to be present in aerosols? Are they infectious is the main thing, you know, in environmental microbiology. We do measure microbes in many different ways. And we can find evidence of them forever. Like if I swabbed all of these desks in here, I'm sure I would find some pathogens. That doesn't mean it's an exposure risk, right? Because they may not be infectious, they may not be viable. So I'm kind of interested in the viability question. I'm also interested in how did they get there? So when it comes to poor wastewater infrastructure, what are the mechanisms by which they get into aerosols and ultimately are transmitted through that pathway? And then what are the risks of exposure? And I'll start out by just saying we started this stuff with a systematic review, which we published a couple of years ago on enteric pathogens and also antibiotic resistance genes in outdoor urban aerosols. And we found 101 studies that have been published in the last, say, 20 years on this question, and really did a deep dive on what methods are being used and what the prevalence and concentration was of some of the targets that we were interested in, both for antimicrobial resistance as well as enteric pathogens. Most of these studies have been done in Europe, the United States, and in China. But so there's not that much data from low and middle income countries around the world. And we found that, you know, a range of microbes are reported, mostly indicator bacteria via culture. Why? Because those are really easy things to measure. E. coli is easy to measure. So E. coli, enterococcus, enterobacter, some pathogenic genera as well, like salmonella. There have been a bunch of studies of qPCR detections of some pathogens, including adenovirus, enteroviruses, and rotavirus. There have been a lot of sequencing analyses of the kind that identified the dog poop in cities in the Midwest that typically resolve microbial IDs to the genus level. And there have been lots of detects via 16S sequencing. Usually what's reported in sequencing studies is just relative abundance. And again, it doesn't speak at all to the viability question. So there's a lot of studies that have looked at this. Um, but the inference for exposure is a little bit, um, is a little bit, uh, limited because for really understanding exposure, we need to have absolute quantitation in terms of methods. And we need to have some information about potential for viability as well. Um, so that's what I was after after this. Anyway, this is our systematic review. I can send you links later. So what's, what was missing or what was missing? we started this work was really quantitative estimation of a wide variety of pathogenic microbes in aerosols, like bacteria, viruses, and protozoa, viability estimation. And I've benefited a lot from new technologies for measuring microbes and aerosols. So I mentioned the Bobcat here as well, which is portable to the field. It's a very high volume sampling device, as well as highly sensitive and quantitative molecular detection. So moving beyond just 16S sequencing to do targeted assays for specific pathogens in multiplex that allow us to get quantitative information across a wide range of pathogens. So one series of studies that we looked at, I'll call aerosol transport of enteric pathogens in cities of poor sanitation. We've been doing this study. We're still working on aspects of this study. Started about eight years ago. And the hypothesis here is that air is one of the pathways, potentially, that microbes get from contaminated sources like feces, fecal sludges, and wastewater. And all of these are sort of well-known transmission pathways. We call this the F diagram, if you've studied this. Fluids, fingers, flies, fields and floors, food and future victims. So we're kind of interested in like, how does this type of source in Bolivia, for example, play some role in the transmission of pathogens through these pathways? And so our methods, we did non-random sampling. We did reference sites close to and far from sources. Um, we used about a 200 liters per minute sampling over four hours with our Bobcat, as well as, uh, impingers, um, which, uh, bubble air through, uh, a liquid medium that, um, transfers the microbes to the liquid. And so you can assay the liquid in addition to ask, uh, Anderson cascade impactors. If you've studied air quality, you may know what that is, uh, for culture. And we've done qPCR, ddPCR, and digital PCR on a bunch of targets. And we collect lots of other data like relative humidity, temperature, wind, UV, other things. And we also sample across seasons because there are some very important differences in air quality and other differences that, like rainy season, not rainy season, that have implications potentially for what pathogens are there and whether they're viable. And the study I'm going to talk to you about in a second is in three cities. So we have La Paz, Bolivia that I mentioned, Kanpur, India, which has those open sewers I showed you, and Atlanta, Georgia, which was our control site. I'm not sure it was a perfect control because Atlanta is like not perfect when it comes to waste management, as Dr. Capone can tell you. We also did really interesting things like this is, anybody know what this is? Anybody seen one of these? This is a this is a. Olfactometer, so this is like a smell sensor that measures semi quantitatively the strength of smells, because one of the things have we always all of us have all wondered, right? Like when you smell a fart, does that mean that there's fecal microbes flying around you? You've thought that, right? It's OK. Like we all thought that. So, you know, one question that many serious scientists have had is to what extent do fecal smells correlate with these bioaerosols, which we know to be present? So I've got a lot. I can talk about that in the Q&A if you want. I won't share the data on this, but it's not a perfect correlation. But this student here, who's now a researcher, was taking smell measurements at the same time as we were collecting bioaerosols at different distances from this supposed source of the Chakyapu River. We also went to really beautiful, pristine places and took control samples. So this is up near a glacier. That's the source waters of the Chakiapu River in order to get some samples that were hopefully not contaminated. What sampling looked like. And all of this, this first paper was published in 2021 that reported some of the data I'm about to show. So this is culturable bacteria by particle size. So if you're interested in the different size measurements of aerosols and how that may relate to the microbial content. So these are control samples up here. And then this is greater than 7 microns over here. And this is 0.6 to 1.1 microns. These are the different stages in an Anderson Cascade impactor. And it looks like, at least for pecal indicator bacteria, that the greatest concentration is in the 2 to 3 micron range, right, around this area. This is La Paz. This is Atlanta over here. We saw some coliforms in Atlanta. But the really interesting stuff is when we started looking at molecular detections via TACMEN array cards. So this is a multi-parallel quantitative molecular assay for lots of different enteric pathogens. And this is just prevalence of positive detection per 2,000 meters cubed of air. So it's a pretty large volume of air. But we saw things like Giardia and Crypto. These are molecular hits, okay? And we saw things like, oh, this Vibrio cholera right here. That's kind of interesting in Kanpur to see that in an aerosol. This is, I think, was the first instance of that ever being reported. And yeah, lots of other pathogens we have here. So including some pathogenic E. coli, things like Campylobacter, then a whole bunch of viruses. Of note here is norovirus, G1 and G2. We typically see that in and around aerosols that are close to sites of uncontained wastewater. And then the black part of these bars is the fraction of detections that have viable co-culture of E. coli in the same sample. And that's because we can't directly measure the viability of any of these pathogens with the methods that we're using here. Like, for example, for the viruses, you would do cell culture for those things. There are other methods for looking at viability of the bacteria and the protozoa. But what we did do is look at, because E. coli is very sensitive to inactivation in aerosols, so we measured that at the same time as we measured these other things by molecular methods as sort of an indirect proxy measure for the potential for these pathogens to be viable at the point of sampling. found a lot of pathogens. And then we also, this is a more sensitive method for quantitative measurement, droplet digital PCR across a number of different pathogens as well. And you can see some of this, these red boxes are around the norovirus detection. So we saw actually pretty high concentrations of norovirus and aerosols in La Paz and in Kanpur. And we saw other things like this is cryptosporidium right here. This is a pretty high level of cryptosporidium in aerosols that we observed, which is also very surprising given the size of cryptosporidium and the fact that it hasn't been reported previously in aerosols. I don't expect you to read this, but we did look at this, all of these detections as a function of distance from the supposed source. So one of the problems with measuring microbes and aerosols is that it's devilishly hard to identify unambiguously where the source of that specific aerosol is from, right? Because it could be from anywhere. It's in the air. Depending on which way the wind's blowing, you could be sampling air and you could be picking up things coming out of the wastewater canal over here or a dump over in this side. So it's really difficult. But one of the things we did was we did structured sampling along a spatial gradient from purported sources of contamination to see whether there was any clear spatial pattern that we could identify. And I would say that generally, yes, we had more positives closer. This is closer over here, zero to 10 meters from the purported source than over here. But it's not like we saw something that's very clear in that regard. Like we saw a lot of pathogens, but we were also sampling in places where there are many sources to worry about. These were our sources in CONPOR. And I should say, let's see. So this is our data from a different study published after the one I just showed you that reports some specific antimicrobial resistance genes that are present. This is genomic copies per meter cubed of air. And these are, so INT1 is a mobile genetic element, and then TET-A, BLATEM, QNRB. These are important antimicrobial resistance genes. And the open circles are greater than a kilometer from an open wastewater canal, and the black circles are less than a kilometer from an open wastewater canal. So you can see that there's a bit of a difference here in some of these specific things we're measuring that may implicate wastewater canals in the presence of antimicrobial resistance genes in aerosols, which is important because those things, the dissemination of antimicrobial resistance is different in many respects, obviously, from like a pathogen target. These things can be readily taken up by other microbes in the environment. So the relevance of these things being present in aerosols doesn't have to do with viability. It's just the gene itself is worrisome if it's being transmitted through this pathway. We also looked at things like dry season versus rainy season. People who study air quality will recognize that obviously a rainy environment and a dry environment are going to have different properties when it comes to the aerosol content of air. And we didn't see any big differences across the cities we looked at between rainy season and dry season. And these are in places where there is a pretty big difference between rainy season and dry season. But we still saw, you know, pretty high concentrations of things like INT1, TETA, and BLATIM, and QNRB. So this is in Bolivia again. This is similar data looking at open wastewater canals. The greater distance is in the open circles, so far away from wastewater canals, and then antimicrobial resistance genes that are closer to those things. We also did spatial gradients here, like before, where we looked at distance from the reported source and our detections, gene copies per meter cubed in air of these different antimicrobial resistance genes and the mobile genetic element of INT1. And we don't see a hugely strong correlation here, but it looks like we did get greater detections closer to these sites. We also did lots of sampling, specifically in Bolivia, to look at the phenotypic resistance profiles of bacterial isolates that we were able to capture from aerosols. Maybe you've seen assays like this is a Kirby-Bauer disc diffusion assay. I see some people nodding their heads. So this is a direct measure of phenotypic resistance to different antibiotics. Like this is ciprofloxacin here. You see this CIP, right? And this is a zone of inhibition around it. That means this microbial isolate that we put on this plate is highly sensitive to this particular antibiotic. Whereas, you know, it's not at all resistant to tetracycline because the colonies can grow right up next to the antibiotic. So we did a lot of that, too, and we did phenotypic resistance profiles. So this is not just what genes encode resistance to different antibiotics, but actually what bacterial isolates are sensitive, resistant, susceptible, or intermediate to different antibiotic classes that are present there. So this is kind of interesting because we could compare this with clinical data to look at whether and how and to what extent microbes that we capture in aerosols are resistant to antibiotics and how that may relate to exposure to pathogens in the city. We're also doing a lot of work right now on risk and dispersion models. So taking this information around how big these aerosols are and what microbes are present to then model the transmission of enteric pathogens in aerosols downstream of sites like open wastewater canals. We've also captured in our work some, we have a few estimates that we've reported that use quantitative microbial risk assessment or QMRA to estimate the health implications, predicted infections as a result of different ways that you could be exposed to pathogens in air. Like on the top, this is we modeled deposition of pathogens on food that are nearby potential sources in places that have uncontained wastewater, as well as things like deposition onto playground equipment and how that would relate then to predicted infections among children who are using that equipment. There's a couple of papers that we have on this. this is one of them that came out a couple of years ago that estimates the predicted infections associated with aerosolized pathogens in La Paz, Bolivia, specifically. So I just want to offer a few observations in summary. So enteric microbes, including pathogens, including antimicrobial resistance genes, they are present and they are enriched near open sewers. A lot of the ones that we have reported in our studies have been previously unreported in urban aerosols, again, because most of the evidence doesn't come from high-burden settings. Many of our samples have viable indicators in many of those, indicating the potential viability of pathogens. There could be a lot of sources. I would say one area that really needs a lot of work is source tracking of aerosols to determine specifically sources that can be implicated. And probably all of this leads to exposures and densities. So if you have a dense city with bad sanitation infrastructure, everything I see suggests that even if this is not the dominant transmission pathway, and it most certainly is not generally, it's still potential, Right. And we need to do more transport and risk modeling. So a few types of studies that I think would really bolster the science in this area, obviously doing epidemiology studies or risk assessment studies that would have to be observational to look at this, to look at the correlation between the potential for microbes to be aerosolized from uncontained waste sites and pathogens in the environment and subsequent exposure to people. I also think, you know, controlled laboratory experiments where we intentionally aerosolize enteric pathogens and look at their viability kinetics is really, really important because aerosols tend to be a hostile environment for most of the pathogens that we're interested in. They don't survive forever in the aerosolized state. And I think the kinetics of that have not been fully characterized. I think there's a lot that we could do with controlled animal studies in the same way that we've done those for the transmission of influenza and COVID through the respiratory pathway. I think a lot of that needs to be extended to some of the other pathogens that we know to be present in aerosols. And I'll just, I think I'm almost done, but I want to give a nod to this study that Jesse Contreras did from 2020 that looked at a network of wastewater canals in Mexico. And it was a very carefully done epi study that I really love that showed pretty unambiguously a risk gradient with distance away from these wastewater canals. And these are places where kids could not access to play in the canals or come into contact with that material otherwise, but showed a 45% lower odds of diarrhea among children living 1,000 meters from a canal, and 24% of all diarrheal disease cases in the study, and 50% of all cases within 100 meters were attributable to canal exposure, given the transport modeling that they did. And so I thought that was, yeah, it's an interesting one. so another thing that we sometimes um note in our studies of cities in low and middle income countries is that wherever you look for fecal pathogens you find them and so one reason why that could be is that there's a steady rain of microbes that are falling on cities where you have poor infrastructure right and i think that is um you know that's potentially behind uh one of the ways that microbes get from one place to another. We know that aerosol transmission is possible. Do we know if it's probable in the case of many of these pathogens? It could be the source of this observed microbial veneer that we observe. So it may have implications for a lot of the environmental sampling we do because, for example, if you take a sample of water and it's in a place where the sanitation infrastructure is not great and you find some pathogens there, that doesn't that it came somewhere from the water. It could come from the aerosols as well, right? So that I'll just say thanks. My funders, NSF, the Gates Foundation, there are others as well. And if you want more information, please have a look at our website. Many of our studies are detailed there. I'll take questions. Yep. Please go ahead. Yeah, no, one thing to say that really a neurological study we need a type of crisis because in the situation in nearby and in Bolivia it's very easy to do that and or even go to the hospital or the health centers and check you know because they have the others and what sort of type of that people, you know, go to bed, help, that could be also useful. Because I think we need to put the health in the context of this. Absolutely. . I like that approach. You need to . That's one question. And the other question is, did you find there's no parasites there? Like Ascari eggs? We've never, nope. No, no. Parasites, especially in Latin America. Oh, sure. Yeah. And we've looked for them in aerosols, but those are so much bigger than everything else, that if they become present in bioaerosols, they probably fall out almost immediately. But you're right. I mean, and I was really surprised to find Giardia and Cryptosporidium in aerosols like that to me is because those are also fairly large, you know, five to 10 microns, which is a large aerosol, right? is not going to be transmitted that far. So yeah, that's a good point. We've never seen, even though we have looked for them, we've never seen helminthegs in this context. And I would say on the epi side, you're absolutely right. What we need are studies that really use the best that we have in terms of environmental epidemiology to show a correlation between air and risk. And the problem is those are really hard studies to do because they have to be observational. We can't do a randomized controlled trial of this particular thing. And it's also true that in high burden settings, the same places where you're going to see these fecal microbes and aerosols are also places where all of the other pathways are very relevant. Exposure to food, water, soils, surfaces, all of the other pathways. So disaggregating aerosols, which are probably a minor transmission pathway, if at all, with all the others that we know to be really, really important, that's a tough study to do, which is why I think one of the things that we could do is controlled animal studies. And I think you can do a randomized controlled trial of these things with animals. You can't do it with people. So I think I would really like to see some animal studies that look mechanistically at the aerosolization of some of these pathogens, their transport, their viability, and ultimately the exposure to the animal model to see whether we can transmit infections via these pathways. Yes, also with animals, studying because the doses of the microorganisms, what that has to do. Exactly. Agreed. Yep. Agreed. And the other thing, like I say, we're doing here is like we'll take these estimates of microbial concentration and viability and build those into risk assessment models, which make use of dose-response relationships between microbes and probability of infection. And we've modeled out these scenarios with deposition on food and deposition on playground equipment to look at, from a prediction point of view, not from an empirical measurement point of view, but just predicting probability of infection to show that, yes, indeed, these are likely to be important pathways of disease transmission if all of our assumptions for the modeling are true but like any modeling our assumptions may not be totally true so i i agree like empirical studies that are used the best epi methods or is what we need yeah yeah so giardia and crypto it's pretty like antimiba like yeah like a meat like like intamoeba histolytica for example we've never i don't think we've identified intamoeba histolytica ever in an aerosol oh i know i've i've had amoebic i've had amoebic dysentery as well and i try not to ever take my work home with me but sometimes i do yeah i've had that i've had geodiasis yeah yeah yes What kinds of pollution, like air pollution? Possibly. That's another black box. Nobody has studied the interaction between specifically air pollution and like, let's just say, things like diesel particulate that you find in the air in cities. and specifically how that may or may not relate to the viability of enteric pathogens that are also present on those aerosols. Nobody's done that work. But I think that'd be really interesting, especially because I think that one of the things that I really want to see are controlled lab experiments that look at the viability of these pathogens in the aerosolized state. And that viability, we now know from studies of influenza and COVID and particulates and aerosols has everything to do with the chemical and physical composition of the particulates and also the characteristics of the air that those particulates exist in. And part of that could be the nature of the pollution that generated those aerosols to begin with. Yeah, I mean, like the places we're studying in Bolivia is like there's diesel exhaust all over, right? So a lot of the particulate air pollution is, you know, is, is, you know, combustion byproducts generated, yep. My question is connected to Dr. Silke Registrar. How will we differentiate the samples collected from the places where we have servers for the like the base ground versus the places we have like the samples were collected from highly polluted area? Also to conjection to this, how we will ensure that the sampling endpoint is like the source? Where is the source? What is the source? Does anybody in here study aerosols? Is that something people study? Air pollution? Yeah. So in air pollution science, What's usually done is a kind of library-based method where you've got a certain composition of metals often that you know to be associated with certain sources, right? So if you take an aerosol sample, you can look at its metal composition and the relative concentrations, and you can say, oh, that's road dust, or that is from a smokestack from a power plant, and that is from a different sort, right? This is soil, right? So we can do that chemically for chemical air pollution. In microbiology, we do something called microbial source tracking. So we find for a given source, and we do this for fecal contamination primarily, like we find a microbe that we know to be present exclusively or almost exclusively in fecal contamination. Then we measure that in the aerosol, and that tells us the aerosol came from some fecal source. but it doesn't tell us which source it came from in the same way that we could do for chemical air pollution. So one of the things that I think needs to happen is we need to apply our best sequencing approaches. Like you could do metagenomics of an air sample and then metagenomics of, you know, shotgun sequencing of all the different sources that you believe could be represented in that aerosol. And then there's a matter of, you know, some PCA analysis or some other type of statistical analysis that could then allow you to infer based on this composition of microbes where it came from. Nobody's done that study yet. If anybody in here wants to write me a check, I would love to do that. Absolutely. Yeah. Right. So I could take these measures in Kanpur and in La Paz and I can say, it looks like we have fecal contamination here. It looks like we have pathogens and it looks like they're enriched closer to this source versus far away but it doesn't allow me to say it's definitely that source that can't be done with the methods that i've that i've used i believe it could be done but somebody's got to spend probably a whole career of science uh doing like developing and applying those methods i mean it's an i think it's enough to say like we know there's a river of shit here and then we find shit in the air like I feel like that is a pretty logical case but it's not airtight, it's not a smoking gun in the same way that I would like it to be So in case you didn't hear, the question was, how do bacteria and viruses compare with respect to their viability in aerosols? And also in our studies, did we look at whole microbes or just nucleic acids? So the first thing is bacteria are far more susceptible to inactivation in aerosols than viruses are, partly because bacteria are far more susceptible to desiccation, which is the main thing that happens in an aerosolized state. So you have microbes that are present in the aerosol, they're drying out, right? They're equilibrating with the relative humidity of the atmosphere, and they quickly become inactivated that way. Now, that's not to say they don't survive for a while, and certain bacteria may survive quite a while in aerosols. But other ones, like these fecal microbes, like let's say E. coli, so your basic fecal bacterium, it's inactivated pretty quickly. It has a half-life in air of probably a few minutes, right? Not that long, which is why it makes it a very good indirect or proxy measure of viability for our aerosol sampling, because it's so quickly inactivated. If we find it culturable there, that means that very likely everything else that is less easily inactivated in aerosols has a greater probability of potentially being viable at the point of sampling. Right. So viruses are probably a lot more stable in aerosols, specifically on enveloped viruses like norovirus, for example. Of all the microbes that are present in wastewater that we think have the potential to be aerosolized, probably norovirus is the one that I would worry about because it's highly mobile, it's highly resistant to an activation, and it's enveloped and it makes everybody really sick. And there's been demonstrated empirical evidence of aerosol transmission of noroviruses like in places like cruise ships. Don't get it on a cruise ship, y'all. Very bad news. But also, and we didn't look at whole microbes, we looked at nucleic acids for the molecular data that I reported. I'm sorry, it's a little bit longer, but we are going to close the seminar now. before we go I'm going to read it for everyone the quote is from Lauren Isley the immense journey in 1957 if there is magic on this planet it is contained in water may your word continue to reveal the unseen, protect the vulnerable and remind us that public health begins with the environments we share. Thank you for your time. Thank you so much. Thank you. We appreciate that. Yeah, thank you. Thanks, everybody.