Hi. So, with this giant room and this intimate group of my dear friends, I don't even need to introduce myself. I always feel like it's a false introduction. For the two of you who are here and don't know me, hi. I'm Dr. Wendy Tanasi. I spent the last 16 years at the VA Palo Alto Healthcare System, mentored by Michael Hodgson up here, celebrated for his third annual retirement. And he, early on, supported me in doing tuberculosis work that's continued to be my career. About five months ago, I moved to Stanford as the chief of what they call Workforce Health and Wellness, which is AHRQ Health. So, I have this, I think this is a super cool, interesting talk. So, I'm glad you guys are taking the time to be here and I really appreciate it. Starting off, I have no disclosures, no conflicts of interest. I'm going to mention a lot of companies. I have no financial relationship with any of them yet. And since the room is not full, I assume none of the representatives are here to offer me jobs. But they're all really interesting. And claims made by the companies are their own and not endorsed by the VHA or Stanford. So, and Steve just told me that because I made this on a Mac, it might translate a little bit strange. In the, what we're going to talk about today, what I want to talk about is the old way of doing TB and what I hope looks like the new way of doing TB, all the way from beginning to end, prevention, all the way through to elimination. Starting with the last 140 years, very little, this is a short little slide, even though it represents 140 years. You all know that in about 1890, Dr. Koch found that mycobacterium was the source of this terrible scourge and cause of death. And soon after, figured out that the TST, the tuberculin skin test, would diagnose TB. The BCG vaccine came on about 30 years later in 1920s. And then I think the big innovations in TB were the antibiotics to treat it in about the 1940s. So now we're 50 years from diagnosis to some treatment. And I put the IGRAs here. I think the Cepheid gene expert is along the lines of one of the great innovations as well. And I put the IGRAs there because look at the gap between the diagnosis in 1890 and then all the way to 2000. We had about 110 years of essentially bupkis. I mean, so Yiddish. So for about 110 years, we had a skin test and no other diagnostic. Come the 2000s and the diagnosis completely changes and we know now who has TB and who doesn't. So where's medicine today? We're in this fourth industrial revolution, which is the internet of bodies. What's the internet of bodies? It's the wearables. It's the implantables. So your personal body data is being uploaded to all of these massive data sets that we're going to talk about. We are becoming the neural network. We are the walking nodes that are connected to each other by our ages, by our heart rate, by our blood pressures. In fact, I wanted to put a slide up here. I was just at a conference where a guy near me in the Bay Area has a non-invasive glucose meter with blood pressure. So he has a watch and you can wear this all over the world and you can monitor people's glucose and blood pressure and hopefully use that for innovation. Anyway, so what is a fourth industrial revolution? So this is backwards, but artificial intelligence is the overall capture of artificial intelligence. A subset is machine learning and a subset of that is deep learning. So artificial intelligence is imitating human intelligence. That's what it's doing. And then machine learning is like you're programming in the machine, like I want you to learn this. And then deep learning is setting up a whole neural network where it actually learns and iterates for itself. We get from that all sorts of great things like digital pathology and integrated analytics and big data. So TB, this is the bat. So a couple of really sad stories and then moving on to what's super cool. In COVID-19, the lockdowns shifted resources from tuberculosis. Think about it, airborne respiratory disease. All the public health workers, all the specialists, all of us in occupational health who did TB were taken over by doing COVID-19. That means out in the world where there really is TB, vaccination by community health workers stopped. Clinical diagnoses stopped from the offices being shuttered. Testing and treatment for TB in high and low income countries stopped. The supply chain disruptions cut laboratory services and supplies and medications for TB patients. Their families lost their jobs and were unable to pay for services. And all the TB technologies and systems that were enlisted to help the pandemic are going to hurt patients with tuberculosis because the program staff and the technologies and even BCG vaccine was co-opted. Do you remember that? We all remember. Were you paying attention when they were like, oh, maybe BCG vaccine can prevent COVID? Gwen remembers. I'll show you what that did. TB hospital wards all over the world were repurposed for COVID-19 and we were all exhausted. And I don't know how many of you burned out and switched jobs. I did, and I think a lot of us did. So I don't want to give that talk on how terrible it is and how dire it is. I want to show you what the cool things are that can happen. But one more bad news. So on the global TB report in 2022, the results of the things I just showed you mean that TB preventive treatment enrollment dropped 30 to 70%. BCG vaccines to newborns fell by over 60%. And remembering that study I just mentioned and the, all the stuff that was in the news, we think BCG vaccine to newborns fell because of the co-opting to try to prevent COVID. So the things that we were doing to save people from COVID are going to kill people from a 10% predicted increase in HIV, a 20% predicted increase in mortality, in mortality from TB, and an over 35% increased mortality from malaria. This is by 2025, representing 10, probably 10 million or more additional deaths from these diseases if we hadn't co-opted all these resources from tuberculosis. And you can see it already. So the trends per country are astounding and they all look like this. They're like hockey sticks. Where we live in California, much of our nursing staff is from the Philippines. So I just grabbed this one, but the rate, they all look the same. TB deaths, this is deaths per year in thousands. And look at that vertical trajectory. We're seeing more hospitalizations and we're seeing more morbidity and mortality from TB in San Francisco already. There's papers out. So that's the bad news. And I, you remember this, like, what is this? Newton's, it's not Newton's pendulum. Newton's cradle. Exactly. Oh, I see my nice graphics get messed up. So what happened is TB, we gave the world all of these resources we had for TB, including the human resources. And then it goes into COVID and everything stops and nothing happens for TB for three years. It just sits there. So what can happen out the other side? Are there COVID innovations and systems that can be effectively leveraged to reimagine TB care? And here's where we get going. All right. What did I say there? Did I say anything good? Oh yeah. Paul Farmer, who we lost of course recently, treat the systems and they will treat the patient. Let's talk about prevention and education. Okay. This is a short one. This is kind of low tech. Johnson and Johnson was really sweet. They gave $200,000 and this is 2020. So the pandemic has already come around. They gave $200,000 for innovations to treat multi-drug or to affect multi-drug resistant TB. The four winners were TB people in Ukraine, Doctors for You in India, ZMQ Global in India, and SHERID here in Philippines. And just to go through quickly, cause I don't, I will use probably half my time. This was a really cool one. This was made by MDR survivors and it's an app. And the point of it was to get rid of the barriers to compliance. So like if an ox cart fell over on the road and you couldn't get to the clinic, you could call this app and the people who were staffing it would literally come out and get you or move the ox cart or, or map you on a different route to your clinic. So it was immediate response to obstacles. And the thing that really touched me about this as well was that shortly after I did this talk first for World TB Day a year ago, um, the website changed. And when I went to look at it, this was what was on the screen. And it absolutely brings me to tears every time. And it's been a year. So obviously they, their war started right around then. And I saw this and it just like killed me and I couldn't even go back to it. And then I went back to it and I looked and do you know that these people were not asking for help? They were offering help. And so you went down into this app and what it actually did was showed people the border, the which borders were open, how long the lines are, lines were at the borders, which routes were open. I just can't even, I can't even believe it. And now the site is down. Um, the other ones very briefly, these were all sort of app innovations, right? And this one's cool because this is actually sponsored by the government of India. The ministry of electronic information technology was part, part of the national tuberculosis elimination program started a WhatsApp telecom consultation program and they used Uber style deliveries. This is the EMQ India, again, app based. And, but this was a whole like packed team. If you have that model in your hospital where they would send field coordinators out to teach people how they could get education on their phone, they'd bring out a mobile phone, they'd show them how to get education. They'd showed them how they can use the medications, use VOT. Um, it, um, empowered the patients with their own adherence and their own education and commuted and connected remote workers. So, uh, and the last one in the Philippines, this one was interesting because it is, uh, associated with a medical center with research. So this was just a video dot, you know, direct observed therapy for MDR treatment. They showed through publications that it was decreasing visits and travel costs and lost work days for these patients. It was increasing access autonomy and privacy and it was designed by healthcare workers to feed research and collaborate with public health. And I bring this one up. This is the fourth one because it was actually acquired by Dimagi and that's going to allow them to really expand their services in the future. And that's the kind of thing Johnson and Johnson can do. Not even just support it locally, but put it out there in the public to be seen and then acquired. So they're all app based, mobile phone based. So like if you think about it, that's really cool and important. And it's obviously the future, but like really, what does it look like? Well, here's what it looks like. It looks like SpaceX. So SpaceX, Elon Musk and Starlink came to the Ukraine right away during the war and prioritized low income countries. And what SpaceX is is super cool. It's the system of really low satellites. So they're only at 550 kilometers over earth where regular geostationary satellites are 35,000 kilometers from earth. And if you even think about the time to transmit, so those are geostationary. So the earth is going and the satellite is following you over a certain location. What the innovation is from Starlink is all these really low satellites. They're still over the atmosphere. There's less impedance through the air for the messages to get to each other. There's less distance from the ground for the messages to get there. And then because it's a network of satellites, it doesn't have to follow you around from this far away. They can all talk to each other. So it's a neural network and it's really quite amazing. And I think it's really going to revolutionize what we do. Well, what we do is occupational health. A lot of us are just in America. I don't know if any international people among the six of you are here. I'm kidding. But, you know, obviously in the world, I think these app based innovations are what really is going to matter. And look, Starlink is coming to Armenia now. So what's changed in exams? Acoustic epidemiology. Does anybody know about this? So acoustic epidemiology is cough classification. So app based, get an app on your phone and it can actually hear and identify your coughs. Here's a study of 1,300 cough recordings. Two third were from non TB coughs using combined sequential forward selection CFS, I mean, SFS with logistic regression and rock curves. The area under the curve is 94%, which is amazing. The automatic classification of cough audio sounds applied to symptomatic patients requiring investigation for TB can meet the WHO triage specifications for identifying patients who should undergo testing. So what does that mean? You're out there in your clinic, you've got your cough app, it identifies you and without needing a health care provider, it meets the criterion to allow you to go get a test. What we need to do, I'll show you, is link all these innovations together. It's a promising and viable means of low cost, easily deployable, frontline screening for TB that can benefit especially developing countries with a heavy TB burden. So you've got this study and it says, okay, cough acoustics work. So acoustic epidemiology, how do we translate that into something that works? Well, HIF-AI, which is Peter Small at Stanford, he came from the Gates Foundation as the TB lead. He is leading this company in Silicon Valley called HIF-AI. It detects, records and geo tracks the coughs in real time. It picks up 98% of coughs during the day. It feeds metadata sets and its vision is it can identify illness and track health. So that's the vision. It's out there. We need something else though, right? We need it actually to work. So this is out of Liverpool. And what they did is they looked at cough acoustics and then they said, how is cough acoustics good enough for tuberculosis detection? And they look at the numbers on the top row there. They're really quite good. 95% specificity, 90% sensitivity, 90% specificity with an overall accuracy. But they wanted it to get better and better. So they did all these metrics and found that the best of all, and this makes sense to us as physicians, is when you combine cough acoustics with symptoms and vital metrics so that this group in India is developing an app or has developed an app that connects cough acoustics with people being able to self-report their symptoms and self-report vital signs. So you put them together now and you've got a diagnostic possibility without having healthcare workers even around. So that's cough acoustics. And that's on the early examined. So moving forward to what is changing in diagnosis? Well, on the sort of what's the non-digital, like the linear, what was it before? What? Yeah, on the analog. Going back to analog, the World Health Organization's 2022 statement included the use of the quantiferon IGRA overseas as a viable test. Quantiferon had been blocked for a long time. It had been black boxed because of concerns about using it for active TB, but the World Health Organization has recognized its importance. There are other IGRAs out there. There are ones from China and ones from other places. The T-Spot is not on the WHO list. But it recommends the use of interferon gamma assays, including quantiferon TB gold, to expand the range of tests available to detect TB. But that's the analog. Let's go to the digital. We talked about deep learning. Remember, there's artificial intelligence and then machine learning. And when you get really precise, you're getting down to deep learning. So it's a subcategory of machine learning that actually learns to pick up patterns and images. So what does that mean for TB? Early on, one of the early deep learning ones, and when I say early, I mean like 2021. Like I didn't include anything that was old. A thousand chest X-rays of TB of patients with and without active TB were split into training algorithms and validations and testing and applied to deep learning models that existed there. They were pre-trained using ImageNet. They found that the best performance came from an ensemble of AlexNet and GoogleNet. Well, there is no ensemble of those two. So it was an interesting finding, but isn't that practical. You can have a net accuracy of 96%. That's in the Radiologic Society of North America. Step it up one, and you get this 2023 report out of Journal of Radiology. Deep learning detection of active tuberculosis at chest radiography matched the clinical performance of radiologists. They had nine radiologists in four different countries versus a deep learning system, now not trained on a thousand chest X-rays, trained on 165,754 chest X-rays, and 22,248 patients. So they trained the deep learning system on that, compared them to the radiologists, and potentially now, without surprise, the deep learning system had a higher sensitivity and equal specificity to radiologists. Those of us in TB, like the chest X-ray really matters, and it's really hard to read, and it's really hard to interpret. And so this is really quite an amazing step forward. Sorry, radiologists. So then how do you take a study that says, oh, this would work, and turn it into something actionable? And that's what this company did. So Cure AI out of India has one of their products is QXR, and this is artificial intelligence for chest X-rays. They trained it on, yeah, 4.2 million chest X-rays. Now we're in deep learning, aren't we? And in less than one minute, an app on a phone, so you're out in a community health center, but you have a basic chest X-ray, an app on the phone or computer in less than a minute can scan that X-ray for TB, COVID-19, and 27 other conditions and assign a risk score for TB. So that's pretty great, right? In studies comparing the AI applications by the Stop TB Partnership, the best group there is, all of the AI apps outperformed experienced human readers, and QXR fared the best. Note that it's less accurate in low incidence areas, as in like the U.S., right? And it's only being used for adult X-rays right now. It's cool, right? Okay, great. So next-gen testing. So what if we use, so next-gen testing. So again, in the diagnostics. Now you can use deep learning with genomics. So do you all know about cell-free DNA? Has anyone heard of cell-free DNA before? No. So this is cool. This is really moving forward. Cell-free DNA tests screen plasma for DNA fragments that are left behind when cells die. A company called Freenome is using advanced deep learning algorithms. Their genomics platform looks for cell-free DNA as well as, it turns out, there's also cell-free biomarkers like cell-free RNA and proteins, and aggregates and decodes the genetic data left behind by the patient's immune system. Now Freenome is mostly doing cancer, and it's doing well in cancer. Now it started out with advanced cancers and being tested against them, and their results, by the way, of this next company I'm going to show you are six hours. Ridiculous. They're in Silicon Valley. So they started out with very sick people with different diseases and tested the genetic models against that and trained and trained them. This company is Karius. Karius is next-gen testing. Again, how do we apply it to TB? This is genomics and artificial intelligence. The Karius test is a liquid biopsy for infectious diseases. From whole blood, the Karius test, and I say reportedly because I'm from Silicon Valley and I remember Theranos very well, detects over 1,000 pathogens causing deep-seated and bloodstream infections. It detects this microbial cell-free DNA that's circulating in the bloodstream. Using the advanced machine learning algorithms, it analyzes the genomic data. It references the genome database and library that's been created, a constantly refined library for its diagnosis of what it claims is 1,000-plus pathogens, including NTMs and TB. I know that Stanford is using Karius. Now, we're using it more for its non-pathogens, like its cancer work, but it's actually here, and this is amazing, and this is where, like, I give no love to Theranos. That was a debacle, and I think at the time we could say confidently that's impossible. Scientists could say it's impossible, Theranos being a company in Silicon Valley that said that they could test over 200, do over 200 tests on a single drop of blood. All different tests, like whether it was microbial or whether it was ELISA or whether it was chemistry or hematology didn't make sense, but this is before cell-free DNA and these microparticles. Now, I think it's possible that the world is really changing. Okay, that's cool, right? How about digital wound care? Have you guys heard about this? Like digital pathology? Well, first, digital wound care. So machine learning is great for repetitive processes. Wound analysis is on par with pathologists in analyzing image-based data. And what they do is they use this computer vision, right? The eyeballs are LIDAR, laser image detection and recognition. You've heard of that, right? Isn't there an opportunity, and I mentioned this to Michael before, for us to do a TST Like of the billions of skin tests that are done, don't we have the technology to do something more accurate than like fake it with the little measuring thing that nobody really uses and they eyeball it to like, it's about three, right? It's about three, maybe? And then we've been proven in all the literature to be very inaccurate in our TST reads. So I actually met with DuPont a week ago for two hours, and we were talking about it because they were looking at the watch that I was telling you about, the non-invasive glucose meter in real time. I sat next to the guy as he was eating dinner and watched his glucose go up and his glucose go down. So DuPont was interested in that, and by the end of the conversation, they actually picked up on my idea of the TST reader and keep emailing me like, what if we used a micro camera array? And I was like, I didn't really mean I would do it, but maybe I would. Because if you think about it, what if we could accurately interpret the skin test? What if we used AI for this? So you could take an image and it reported an accurate measurement. It would lower human error, it would reduce healthcare worker workload, and also people wouldn't have to return for their second visit. We could scale up LTBI evaluation volume and have automated reporting, because one of the problems with the TST is it's manual, it's text file, right? It's TIU data. It's not generally findable in a database, but it could be an automated reporting. And I thought that was pretty cool, but that's just my idea. So that was because of the wound care that's come out digitally that's so good. What is proven for TB already is digital pathology. So using something similar, which is lesion image recognition analysis, tuberculosis pathology is being proven to work well with diagnostically. They're using mouse TB lesions. The Journal of Thoracic Disease in 20, this was earlier, 2018, examined against the double confirmed diagnosis by pathologists using microscopes and digital slides, AI. And AI had a 98 percent sensitivity and an 83.5 percent specificity. And this is digital pathology for diagnosing tuberculosis, pathologic specimens. All right, moving from diagnosis to compliance and treatment, drones, right? This is great. One of my neighbors is working for this company. Launched in 2016 in Rwanda, the goal of this zipline company was to deliver blood to remote areas, which is particularly important, right, for pregnant women or delivering women who are hemorrhaging. And what they have done to save women's lives is really amazing. They are now at over 10,000 hospitals. They've flown over 40 million miles with their drones, which is 80 times to the moon and back. They're in six countries. They just opened in Nigeria. And they have shown, in hindsight, since they opened in Rwanda, that vaccinations were up by 86 percent. So they started delivering blood, but they're also delivering vaccinations to remote clinics, especially ones that are not heat-stable, so you can get them out there in a matter of minutes. They're delivering medications and other things. What are they doing for tuberculosis? There are studies like PLOS ONE, good journal, Drones and Digital Adherence Monitoring for Community-Based TB Control in Madagascar. And this one I just showed you about digital pathology. They're bringing pathologic specimens in to centralized pathologists. Soon they won't need to do that, right? Because they'll all be digital pathologists, they'll just be AI. But this is what I'm talking about. We need to link these different interventions together. Instead of even droning your sample in, you can actually have an AI reader read a pathologic specimen right now. So here's the video. So here's the drone. It has about a 10-foot wingspan, 3 meters, and it can carry about 3 pounds, 1.75 kilograms. The plane is measuring actively the wind speed and the direction. And so if the wind's blowing in a particular direction, it's going to compensate and drop that package so it lands on the ground right where you want it. We can hit an area about the size of two parking spots. It looks kind of like a cake box with a paper parachute on top. A fixed-wing aircraft can fly dramatically farther than something like a quadcopter. And that's really important for what we do. It can fly faster, it can fly through heavier weather, and the approaches to things like safety are also much easier. On our aircraft, for example, we have multiple motors, right? The plane, if either one of those stops working, the plane flies just fine. We're in Rwanda today, and we're expanding to cover the other half of Rwanda as we speak, and next is Tanzania. From there, we are really focused on solving this problem, access to medical products at a global scale. There's access to medical product problems in the U.S. and in the developing world, and we really want to solve all of those problems everywhere. So did you see the drone stopping? Did you see it being caught like an aircraft carrier by that wire and then swinging down? They tested all these different landing mechanisms, like, you know, blow up airbags and things, and they were crashing drones left and right, and they ended up with this catch system with this hook. And it's pretty crazy, but it is really working. I mean, 40 million miles flown and countless lives saved. So now you get a zip line, you're out in your remote area, and your medications have been delivered to you. What technologies do we have once the medications are delivered? Well, there are these adherence technologies. Here's a smart pillbox. So this smart pillbox reminds people to take their pills, informs their healthcare workers if they don't, which is funny. It has a battery, a chip, a charger. It lasts three years. The idea is that you can spread it around your community and use it over time. It has an app with a camera in it for video DOT. You can see the ports there for charging. There are studies going on for more advanced compliance testing, but unfortunately, one of the studies' countries was Ukraine, and so the study is a little bit behind where it needs to be. But the data plan is prepaid with the SIM card, so now you can actually drone out the medications and watch the adherence through a smart pillbox. Well, what if you have MDR patients and you're delivering Bedaquiline, which is the antibiotic which is used for MDR, which can theoretically, though I think it's not playing out as well, cause death in people with QT prolongation? What technology do we have for that? Not to worry. So there is this company called Cardia that has a little device. It's about this big. I just saw it at that recent NextMed meeting. It's about this big. You put your two fingers on the silver nodes there, set it on your left knee, and it loads a six-lead EKG to your app on your phone. So you can read an EKG right there with this little thing. It's quite elegant and quite beautiful. And then you can see if your patient has QT prolongation or not, or it reads it automatically, says no QT prolongation, and you can give them the Bedaquiline. The next gen that they have coming out that they just showed at this conference is a credit card. You can stick it in your wallet. You can put your thumbs on it, and you can get an EKG off it. So if you're in the first world and you suffer from different arrhythmias, you can read it like that. If you're in lesser-developed countries, can you imagine? You don't need a cardiologist to read it anymore. You can use these little credit cards. Thin and light. Portable doctor's office, they call it. That might be a little bit excessive. All right. So moving on from diagnosis and treatment to vaccines, actually, I'm going to maybe go out of order. Gene therapy. So why not, right? So these are recent. There's a mutation in the TB gene associated with drug tolerance, meaning that a thambutol resistance has been found in the genome, and we're using CRISPR to cut it out. Because why not, right? We can do these kinds of things. So you can actually make people more susceptible to a thambutol treatment through gene therapy. And I'm going to go backwards, because I put these in out of order. Everybody would want to know where... So gene therapy and CRISPR is super cool. That makes people who have TB more able to be treated, but as Gwen pointed out to me this morning and wanted me to emphasize, I talk a lot about treatment, a lot about diagnosis, but the only solution to tuberculosis is an actual vaccine that works. So where are the mRNA vaccines for TB? Haven't we all wondered through COVID what's going on? There was actually an mRNA vaccine that was shown to protect mice against TB over 15 years ago in 2004, and it was actually part of the proof of concept for the current COVID-19 vaccines. It was a subcutaneous injection in mice. Four mice, four times, Q3 weeks, showed that it was significantly protective, but less so than BCG. So not good enough. But remember, this is 2004, and everything about technology and ideas are when preparation meets opportunity, or when opportunity meets preparation. So if you've got an idea, but the preparation, the infrastructure isn't there to support your idea, you can't realize it. So in 2004, they were ahead of the curve. Now what do we have? We had that mRNA vaccines were expensive to make back then, but manufacturing costs have fallen dramatically. We have a little, we actually have knowledge now that pure mRNA is actually highly stable, and that you can freeze dry it. The problem is you just have to be able to rewarm it safely, so you've just got to get a heat-stable adjuvant in there, because we're never going to be able to deliver a TB vaccine out into the lesser-developed countries if it has to be in cold chain storage. So this is all possible, and I'm sure it's coming. Can the stunning successes of mRNA vaccination against COVID-19 be replicated for TB? Again, what I'm talking about here is all these innovations that really came out looking at COVID-19 that are being repurposed or should be repurposed for TB. We talked about gene therapy, which is amazing. There are actual TB candidate vaccines out there. We're getting right to the end. This is a New England Journal article in 2019. This was the phase two trial of beautifully named M72 slash AS01E. I'll be right up there on the tip of my tongue in the future. The New England Journal article showed that it was safe, and interestingly, it provided 50 percent protection against active TB disease over three years. And it was particularly effective in individuals with no evidence of prior TB infection. Think children, right? In providing 90 percent protection against active TB disease. The phase three trial is currently underway, slated to be finished at the end of 2023. That'll be amazing if that works. Okay, so let's say we get this great vaccine. We have the drones, but how else would we deliver vaccines? Are we really going to send needles and biohazard boxes and dispensaries out there? No, because we can 3D print vaccines, actually. So transdermal vaccination via 3D printed microneedles works just as well. Of course, this was shown for COVID. This company is in Australia, Vaxis, and they used it widely. Here, more locally, the DECA, sorry about the circle, the DECA self-administered patch. This is a 3D printed microneedle. You send it out in this packaging, peel back the packaging, pick up the little thing, stick it on your arm, and consider yourself vaccinated. Unbelievable. I just think that is absolutely extraordinary. They had actually done some early BCG testing in 2011 in guinea pigs that showed that you can use microneedles for cellular immunity, but then again, the rest of the technology wasn't there to make it work. So getting down to the end here, how are we going to eliminate things? We need to aggregate data, and we need that data to be accessible. This is hilarious. These are the World Health Organization official apps for tracking COVID. The two ones that they approved were health weather and sick weather. I thought that was pretty funny. I guess I'm easily amused. How do these work? These crowdsource over 6 million illness reports a month in real time, and you all saw this in COVID, right? You all saw these apps. You all saw these heat maps, but look at what you could do with a heat map for TB, and what could you do with contact tracing? Why couldn't we use something like this to detect TB cases and therefore their exposures, right, and identify the cases and predict the hotspots? It's not there right now for TB, but it should be. It looks like it would be quite easy to do. Databases were built so that the world could share their information on COVID, but less so for TB. The World Health Organization put one together for TB as like a little sister to COVID, so you could only put the publication in there if it actually had to do to COVID, and oh, by the way, they have TB. So they did a digital library of TB and COVID-19 publications with case studies and programmatic innovations and ongoing research projects and studies. So that is available. We should have a TB-only one. Okay. So that means, for goodness sake, Wendy, stop talking. This is the Stop TB Partnership. What could we do today? You know what I'm going to say. We can test for TB. For those of you who are from the United States, we know where latent TB is. We know who has it. It's our non-U.S. born. We have the means to treat it. We don't even need all this fancy stuff because we're in the first world. So if we test them with an IGRA and we treat them with the short course, like 12 days of antibiotics, we can eliminate TB in the U.S. We are so close, but you know how 90% of the problem can be treated and it's that last 10% that's so hard? That's where we are. We're at the last 10%, but innovations have gotten us here. We have IGRAs now, and they work, and we have short course therapy that doesn't have the side effects, doesn't cause the hepatocellular toxicity. It works. People are compliant. So we can eliminate TB in the U.S. with things that we already have in place. Final slide. Summary. Decreasing worldwide TB has made real strides in the last 130 years, but look what just happened in the last few years. COVID-19 pandemic started to set us back on those advances, right? We know that we're in for a slingshot effect. We're going to have worse global health than we've had in 100 years in the next five years, and that setback could last a decade, but in this era of healthcare transformation, we have unprecedented access to progress. The social and economic disparities will continue, but TB advocates like us need to capitalize, digitize, and help revolutionize to create a healthier future for everyone, not just us, and I would say the best is yet to come. That's all I've got. Thank you. Thank you. Sweet. I love the applause. They're all my friends. All right. I know that was a lot. I think it, I hope it was just kind of cool and fun and interesting. Any particular thoughts? I don't know that I can even answer any questions because it kind of stretches me, but what have you guys seen or experienced that you have liked or enjoyed in the last few years and thought maybe it can transform what we do in OH and in public health? Has anything come out that's like transformed the way your practices work? Hi. Hi. Francesca. Hi, Francesca. Ford Motor. I'm really curious about your thoughts about what we could do in the broader field of occupational health, you know, in this leapfrog method, right? What else can we do with these devices? Can we, you know, we can take vital signs, what kind of medical surveillance can we do? This idea of AI with x-rays for medical surveillance is awesome when you think about pneumoconiosis. So what else can we do? Can we train people to wear respirators using videos instead of, you know, can we use AI to do particle generation and do respirator fit? What can we do? I love it, Francesca. I think you've got more ideas than I do. No, I really do. And I think one of the things that holds me back is the unending frustration at living in the first world in this fourth generation of medical care without an electronic health record. Like, how is it that I live in Silicon Valley and we're still on Excel and paper half the time? So while we've got amazing opportunities and potential, I don't think we're going to get anywhere really meaningful in occ health until we can get a really good electronic health record and aggregate our data. So like the NIOSH ODH project, which God bless them, they've been working on 15 years. Couldn't we have found silicosis and this consequence earlier if we had known people's occupations and could tie it to the fact that they were getting pulmonary fibrosis in 35-year-old, you know, Hispanic people? Like, why is this all of a sudden happening? Couldn't we figure out, I mentioned to Dr. Hodgson, who just had to go, that we seem to be seeing cataracts in the operating room in our surgeons because their eyes don't have lead protection, their thyroids and axilla do, their chest do, but their eyes don't. And we're seeing early cataracts. But they're going to their primary care doctors, they're not going to workers' comp for that. If we knew their occupations and we could identify the diseases earlier, that would be a big transformation for us. So getting the occupation as part of the basic primary care record would be really great. It's a ways away. Also getting us on an electronic health record where data is aggregated and we can look at things regionally, we can look at best practices. I think that's one of the most important things for us to try to do here. But I love all your other ideas. It's going to be bits and pieces and then putting it together. And like what I gave you, I think what frustrates me is, this is so cool, like I think every bit of it is cool. Like what? Acoustic epidemiology? What are you talking about? But it's an isolated thing. We need the World Health Organization or Gates or somebody to come in to each of these individual companies, line them up for TB and say, you need to work together or we're going to fund this pipeline from beginning to end. Once we've got the diagnosis, we're going to drone deliver you the meds, you're going to check that you don't have QT prolongation, you're going to use a smart pill box to make sure you've taken the meds. You know, like we could string together each of these to completely transform health care. That's what I would do out in the world. What you got, Sonia? Hi. Hi, Wendy. Thank you for this fabulous talk. I love this. This makes me think about what is possible in terms of triage and having people self-triage their illness in the field in remote places. And then what could we do to expand the reach of occupational health, of occupational medicine physicians to reach the people who need help? That's really interesting. Yeah. I think the internet of bodies is going to help us. I think one of the things I liked about this wearable watch with the non-invasive glucometer is that the range is 60 to 190. And who is at 60 to 190? The pre-diabetics. And what does an employer want? A healthy workforce. So if we start using some of these wearables as early interventions and get employers to provide people like they used to provide them with Fitbits, right, with some of these devices that show blood pressure and glucose, we could intervene in all sorts of remote places because people have charge of their own health. And so they're not very expensive. This watch right now is like $250. And it's not available to the public yet. They've got like 7,500 of them that are out in the public. But I think that's the kind of thing where we could really get our reach out there because we could be helping our workforce take control of their own health. And we could be selling this to employers as a workforce wellness opportunity and interacting to keep them present and healthy. That's the first one I think of, but I bet there's a million other ways. Other questions or thoughts? We're late? Or early? We're late? Right on time? Early! It never happened before in the history of Wendy Tenassi. Thank you. Thank you very much.

TB prevention

TB diagnosis

TB treatment

TB vaccine development

Internet of Bodies

wearables

implantables

data aggregation