Okay. Thank you so much. Thanks so much for the invitation to share some of our work on school wastewater monitoring in Houston, Texas. This is really a collaborative effort led by the Houston health department and in collaboration with us here at Rice University. Okay, make sure I can control the screen. There we go. Okay, so just as a quick overview and to give some context for our school wastewater monitoring program. It lives within our larger monitoring program where we sample from 39 wastewater implants, lift stations, but actually the majority of our sampling sites are facility level. So we sample at 75 manholes and the majority of those manhole sites are at public schools. So about 50, 52 public schools are sampled weekly across Houston. And so this map here on the right just shows all the sewer sheds and different colors and all of the facility level samples are shown as little dots on this map. So I'm going to focus on the school monitoring and really the motivation behind this is that respiratory viruses are a leading cause of hospitalizations in children. And previous research has actually shown that schools can be sources of respiratory viral outbreaks within communities. So there's really an interest in better more rapid and just additional surveillance in school settings because existing surveillance systems are likely under counting cases, especially with some of these diseases that might be low have low, you know, asymptomatic in children. So here is a map that shows where we're sampling from schools across Houston. We have three kind of clusters of schools across Houston, this North cluster, Southeast cluster and Southwest cluster. These schools were identified to be part of this program back in 2020 and we're setting it up because they were all located in zip codes with high positivity rates. And in terms of how long we've been doing this, you know, we started doing wastewater monitoring at a citywide level in March of 2020, right at the beginning of the pandemic. And then by December of 2020, we were sampling from these 50 or so schools and analyzing the wastewater for SARS-CoV-2. So at this point we have about two and a half school years worth of data for SARS-CoV-2 from these 50 schools. And since then, we have added on additional respiratory virus targets. So in September of 2021, we added on influenza. And then in September of 2022, we added RSV. So we have about two and one year of school data for those two respiratory viruses. And now we're also thinking about and working on expanding to additional targets that are not just respiratory viruses, which I'm really not going to talk about right now, but I'm happy to talk about in the discussion. In terms of how these samples are collected, we have refrigerated autosamplers actually located in manholes that were identified in collaboration with Houston Public Works that only get wastewater from those schools. And so these refrigerated autosamplers sit either within a manhole right outside the school or adjacent to it. And these are programmed to basically collect a sample every 15 minutes to create a composite over the school day or approximate school day. So they run generally from about 6am to noon. And then a team of Houston Health Department staff actually drives these routes to pick up these school samples once per week and then drop those samples either at my lab or the Houston Health Department lab where they're analyzed. So now I'll get into showing some of the data. This, these are heat maps that are showing the detections of the three respiratory viruses. SARS-CoV-2 influenza A and RSV over the 2022-2023 school year. So the schools are shown on the Y axis and then the date is on the X axis. And if we detected that disease target for SARS-CoV-2 it's shown in red. It's purple for influenza and red again for RSV. If it was below the detection limit, it's shown in blue or green for influenza and RSV. And then if it was inconclusive, which means that usually one replicate was positive and one replicate was negative. So typically you're right at that detection limit. It's shown either yellow or pink. So as you can see, especially for, you know, SARS-CoV-2 we had the most detections. Levels were generally higher for SARS-CoV-2 than for influenza A and RSV. The majority of the samples for influenza A and RSV were negative, but you can definitely see that there was this surge in time that occurred really around that period when we were experiencing what the news was talking about in terms of the tridemic. And so we saw really this concurrent surge of influenza A and RSV in the schools. And actually SARS-CoV-2 lagged a little bit in terms of when we saw a surge of SARS-CoV-2 across the schools. So to better understand and assess the value of the school wastewater for understanding infectious disease spread, both in that school but also in the broader community, we asked a few questions of our data. So the first question that we asked was whether wastewater levels were indicative of an infection in the schools. So to do this, we worked with the available clinical testing data that we had. So we're lucky in that the Houston Health Department was also running a free testing program for COVID-19 in the 2021-2022 school year, where they offered free testing at 46 schools and they had 13 weeks of this. Of course, parents had to consent to have their kids participate. And even if the parents consented, then they actually did have to participate. And so while this was great to compare to is actually a pretty sparse data set and probably a pretty limited clinical testing set to compare the wastewater to. But when we looked and we compared, we use logistic regression to compare the wastewater concentrations for the schools that also had this paired clinical testing data. We did, in fact, see this significant and positive relationship between the concentration of SARS-CoV-2 in the wastewater samples and the probability of a positive test at the school. So even with this imperfect data and that the testing was nowhere near comprehensive and most of the, and obviously the uncertainty of whether, you know, in 2021-22, we weren't even sure if kids were going to be using the bathroom and whether we were going to get a signal. We did still see this, this significant and positive relationship with which gave us some confidence that the wastewater levels were indicative of infections within the schools. The next question that we asked was whether the wastewater concentrations at the schools were reflective and associated with the positivity rates of the communities. So here we aggregated the schools based on what zip code they were located in. And then we looked at the average SARS-CoV-2 concentration in those schools within the same zip code. And then we compare those to the zip code positivity rates. So, and again, we saw this significant and positive association between the concentration of SARS-CoV-2 in the school wastewater and the zip code positivity rate. So this is showing that the schools are actually reflective of community positivity rates. And we've done this for two school years now. I'm just showing the 2022-2023 data, but we also did this for the previous school year, the 21-2022 school year data. So finally, to also look at our influenza and RSV data in a similar way, there was much less clinical testing available for influenza and RSV. And so to compare our school wastewater data to other existing surveillance data, we decided to look at syndromic data. So this was if you go to an emerging department or a healthcare testing facility and you get diagnosed with something and you have a discharge diagnosis of either influenza or RSV. We looked at the percentage of those visits that were discharged diagnosed as influenza and RSV. And then we compared that rate of discharge diagnosed influenza to the proportion of the schools with positive wastewater detections for both influenza and RSV. And we did see this positive and significant association for influenza for the city-wide influenza rates and the number of schools with positive detections. And we also saw a positive relationship with RSV that was not significant. This was really largely due to the autocorrelation and the time series data. But this lets us see, okay, not only are the wastewater levels reflective of infections at the school, infections at the zip code level, but also reflective of kind of city-wide levels of disease burden. And so we think about selecting sites that could be used to tell us something about not just, you know, facility-level infections, we could also potentially use schools as sites to tell us something about community-level infections. And so I'll just have a couple more slides where I want to talk about how this data was used by the Houston Health Department and Dr. Purse is on later, so you can talk a lot more about this. This school's results are reported back each week to the nurses, to the superintendents. And during the peak COVID emergency period, the health department really used the schools as a springboard into the community to encourage vaccinations. So this is just a picture of a fact sheet that's put together where information about school detections, school wastewater detections was shown alongside vaccination rates for the communities. And they would use this information to try and encourage folks to get vaccinated. And another thing that was done is actually free vaccine clinics were held at two of the elementary schools that are participants in the school monitoring program, Lions Elementary and Barrack Elementary where they offered free influenza and COVID vaccines at these schools. And then members of our team have also done a study where they've looked at and tried to understand how wastewater data is used by a range of stakeholders. To make decisions and to strive and drive actions associated with COVID-19 prevention and mitigation within the schools. And one of the main findings that we came away with from the study was that maximizing the utility of wastewater surveillance in schools will really require educating school staff about what wastewater data is, how to use it, where to find it, and improving communication with the stakeholders that are receiving this information. And so one example of something that the health department has done with this data is Dr. Purse held this webinar with school nurses, where we actually walk through kind of how to interpret the school wastewater data. And at the end of this webinar, he also surveyed them and asked them, you know, how is having a better understanding of wastewater and its implication or is having a better understanding of wastewater and its implication helped me understand to plan and implement strategies to reduce the risk of COVID-19 infection on my campus. And most of the participants responded with agree or strongly agree, which was really a positive feedback from the stakeholders on this program. So we're really focusing now on how to continue to improve communications to schools and work with schools so they can interpret and use this information from the wastewater. So with that, I will conclude and acknowledge that this is really the work of a large amazing collaborative team, Dr. Hopkins, Dr. Enzer, Kelsey Catten and Julia Shudler helped with the analysis that I showed today. And we've published some of this work in water research if you'd like to read more about it. And I'm happy to take questions at their time or wait to the end when we have a discussion. Thank you, Lauren. I'm going to use the chair's prerogative and get one question in and then we'll hopefully have time for others at the end. One of the things because you did multiple schools. Have you looked what would be the most, I guess the most efficient number of schools that would give you the same outcome data. That is, you know, it would just put imaginary budgetary constraints on this, you could only test a certain number of schools. Did you look at that in terms of what would be kind of the most parsimonious approach to giving you the same data from a community perspective obviously wouldn't give you the same data from a specific facility. But in terms of the community, did you look at like, could you just pick one school instead of four or five. That's a great question. I don't know if we've done the analysis to answer that, but we definitely see very different patterns of detections at the different schools. So there's some schools that are, you know, almost always positive, which is, and then some schools where it's pretty sparse. And so I think we have a lot more work to do to understand why that is, you know, about anything from like, you know, the sampling to the, to the populations that we're serving and so I think, you know, we'd have to take that into account and I guess my question would be like, what would we be comparing it to the community level positivity rates is what you're thinking about. Yes, this is the right number of schools to capture. Yeah. Right. So, so now using the schools basically as, as sentinel sites reflective of the community, rather than telling you what's happening in that school. I realize that's a different purpose. But it kind of comes to this larger question of, you know, how you, how you allocate your resources most efficiently. Yeah, I think that's certainly something we could look at. Yeah, I think you're right in that this was largely set up. Not really at the Sentinel site study but where the help serve the schools, but if we needed to pare down and think about maybe one school is representative of all the schools in that neighborhood. You could do that analysis and try and cluster them, maybe at a more finer geographic level and see if that hypothesis is true. Yeah, exactly. Okay. We can get back to that question. I think it's really interesting in your data certainly would shed some light on on that big question. Let's move on to the second presentation which is monitoring correctional facilities in Ohio and that's going to be presented by Mark we're so mark some kind of security alert just ignore that. Right. I should have control and power. Your slides are showing up great. Great. Alright, so thank you for having me. With regards to this a lot of the learning that we did in correctional facilities is not moving. There it is now. A lot of the movement that we did in correctional facilities was also some other things that we were learning in other locations like on campus. A couple different study sites in Louisville and things like that and it's going to be talking about as a kind of a combination of those and then bring it back specific to. Well, we have found effectively as best practices for. Department of rehabilitation and correction. So if you see. That's Ohio Department of rehabilitation and corrections. There's 33 correctional facilities that are all being monitored. Either twice a week sampling composite sampling or. Uh, ramp down to once a week sampling or some of them where. COVID effectively disappeared along the way. As a general. Refresher to an extent what I'm going to be talking about is much more on the mathematical computational side of things. So I'm not going to be showing any data. I wouldn't really be able to show any data. Since it's for correctional facilities, but. It's also not really what I'm, I'm mostly focused on. But effectively you have a population that's shedding out. Sars Cove to signal we find that using molecular methods. We're still using. Quantitative methods for ODRC. So everything's still run through digital drop of PCR. There are some investigation that we're doing elsewhere. For the passive samplers for effectively qualitative data. And we're test betting the analyses there before we integrate that into ODRC because that way. ODRC doesn't have to spend extra money on more sampling. Just to look at the passive samplers. Once we go there, what we've been doing is trying to build a digital twin. We've been trying to effectively say. From this signal, what does that inform us? So we've been testing. Number of different algorithms as well as mechanistic modeling. Mass balance approaches seem to be doing really quite well overall by way of what we're, what we're able to estimate. But they're, they're a little tricky to develop properly and then optimization can be a little, little challenging. One thing that we did learn is being able to figure out whether or not you have a sample of convenience or if you have a targeted sample. So when we're talking about a correctional institute and you can't really show you a map for obvious reasons, but imagine a cluster of buildings in one section. And then some apocmark other buildings and that's all within a fence wire. So anything inside the wire that is the correctional facility housing area. And then there are administrative offices. There's correctional officer offices. There's visitation areas. There's all these other other areas that are not housing. And then housing is where a lot of the environmental controls get put in place. So when we're looking at using wastewater based epidemiology or wastewater monitoring to be able to understand what it is that we need to try and do moving forward to either improve overall health within the correctional facilities. Or to limit spread. So the, the main purview of, or the main focus of everything within Ohio department of rehabilitation and corrections is for the safety, the care and the actual rehabilitation of offenders. So there's a lot of different on the job training. There's off job training. There's educational resources outside of job training. There's a lot of different substance abuse, excuse me, substance abuse, rehabilitation and care that goes into it. So there's a lot of communal activities that need to be maintained because the point of a correctional facility is to try to drive towards rehabilitation of somebody who has offended in breaking law. So that is the paramount operation of it other than keeping them safe and keeping them healthy as possible, which is challenging because it's communal living and a lot of them. So do you ever hear a term open bay prisons. Just think of like a classic military barracks. That's effectively what you have. So, and what we've been focusing on primarily is trying to look at multiple ways of signal processing. So we have a time series that's coming through and everybody understands basically what that means is that you have a, you have a signal that's originating into an environmental media based on time period of when it gets shed into the wastewater. The challenge that is interesting and that as we start unpacking it, we're able to do a little bit better on using these data in the overall risk management scheme of ODRC. So what we've landed on that that's most reliable is any number of different flavors of a moving average. They're, they're fairly simple. There's not a lot of complexity that goes into how they operate. And they do just as well as a lot of other options. There are other approaches that we've been experimenting on with regards to approaches. Now that we have reams of data coming through and we can match that over to human testing as well. There's a lot of different options that that opens up, but in reality, what it effectively is and I'm kind of demonstrating it here is you have effectively two different signals based on when you're doing your sampling and then you start compounding that further. So it will be X then Y then Z then on on you go for each snapshot that you're taking overall. And we're accumulating those as an overall aggregate signal coming through, but they are coming from the same fundamental source. But remember what I said you have the housing units within a correctional facility and then you have the actual buildings that are maintaining and operating it. Where do you want to try and set your focus we can't actually put an auto sampler at the outfall from each one of those buildings because the manhole covers are welded shut so nobody escapes through the sewer system. So we can't actually get a sampler down in there so we have to be able to look at it from where the signal coming through to where we can actually sample it outside that wire. And then try to trace that back to housing, because that's where the majority of our environmental controls are when we're talking about risk management. So, what we've been able to do with regards to how we operate within ODRC is that we have some fairly strict constraints. We really can't, you know, so we have to fit everything within our overall risk management framework so. Masking is not something that is either ideal or possible depending on the level of security of the facility that we're talking about. Also, there's enough stress in this environment in and of itself, both from the offender population as well as the correctional officer population that. Having that additional barrier of having everybody in a mask is just not something that's conducive to safe operation of correctional facility. So what we've been doing is we've been making sure that the wastewater is either a confirmatory or a leading indicator of any changes that we need to do with regards to all other environmental controls. ODRC has a ramp up ramp down risk management policy that wastewater monitoring is a critical component to. And when we ramp up, we control how we're actually kind of moving people around into which job categories, how they line up to be able to get the job categories. Whether or not the commas area is open, whether or not the barbershop is open, how many people can go through. Those are all population and some level of environmental controls that we have that wastewater will help indicate whether or not they need to be ramped up. Or whether or not we're in enough of a safety margin where they can start getting ramped down. So that's why a robust risk management plan. It was a critical step to being able to use WBE or wastewater monitoring in a much more realistic and efficacious way for ODRC.  But anyway, there's the weir method and the weir barrier. It's just ways of having offenders sleep in an open bay prison. And then there's a barrier in between that we used a couple of different modeling approaches and then wastewater as a verification point about whether or not these things are actually working. There's a lot of different ways of being able to control it, but wastewater is a nice way of getting an aggregate overall view of what's happening within that population. As we're trying to move through these different hierarchy of controls, we need some kind of evidence that will get us there to move forward. So the way we operate it is we have the monitoring data come streaming in to a Monte Carlo algorithm or Monte Carlo simulation that we're also now testing recursion methods to be able to try and get away from the Monte Carlo. Monte Carlo is an iterative process that just takes a lot of time, the more data you have streaming into it. So what we're trying to do is trying to look at some recursion methods that would be able to get us away from the Monte Carlo. So this is going to run a lot faster. If we get to a point where it's going to be an emergency again and we need to make decisions quickly. I'm trying to go to the next slide I don't see that's going. Oh, did I go too far. I missed a slide. So, yeah. Okay. I must not send out the one anyway. So, where it's where this is going now into the future is two different areas. So, where ODRC is interested in is being able to support this ramp up ramp down concept. So, how do we improve being able to ramp up and ramp down different controls? Is there a way of being able to incorporate other infectious disease agents that we may be concerned with? Again, it's communal living. And a lot of the open base settings because when you're at a minimum security level, you can have these more open bay types of settings. Excuse me. What is also somewhat challenging or what's also the next piece to this is again trying to get ahead of what that's next evolutionary step is for SARS-CoV-2 or if there's another one that we coming down the line. Right now ODRC is not really doing discovery with regards to that, but they're interested in being able to incorporate it. So that's where a lot of it. Other work of well, how do we actually use forward thinking and forward looking wastewater monitoring to say what's the next possible epidemic or pandemic level threat computationally so that they can integrate that much more rapidly. That's another piece where they're quite interested in looking at. And the other one is where they significantly expanded out to drugs of abuse. So, like I said, the Ohio Department of Rehabilitation Corrections takes corrections and safety very seriously. Drug use and drug sales inside of a correctional facility are highly dangerous business and all as well as activity. What we're trying to do is make sure that people who have a history of using drugs that leads to criminal activity outside of using the drugs as well. Obviously, can be limited by getting them clean and sober on these aspects. So what we started to do is expand this out looking at the same time in the same locations for cocaine, methadone, methamphetamines, oxycontin type of codeine and heroin. So what we're seeing is overall, well, with regards to infectious diseases, there isn't really any kind of correlation. And we wouldn't expect one on that, but that's one of those next steps where they're taking wastewater monitoring is what infectious agents should we also be concerned about getting ourselves ready. And they want to ramp up ramp down type of risk management plans. And then where can we move this for all of our other priorities such as drugs of abuse and other things that we're trying to control. I'll leave at least some time for questions. And if you need my email, I think everybody has my email, but if you need it is on the last slide. Thank you, Mark. We might be listening one question in if there if someone wants to raise their hand. Stephanie, do you see any questions popping up? Nope, not yet. So we'll we'll have additional time for questions at the end as well. Yep. Let's move on. Thank you very much Mark. So our next speaker, Rachel Paretsky, who's going to speak to us about airport monitoring. Super. Thanks. I also. Yes. Okay, great. So I was also asked to comment on other sentinel surveillance and healthcare facilities in the context of antimicrobial resistance. Again, so I'm super briefly going to mention that, but we can talk about that more at the end. There we go. Okay. It just takes a second.  These are the core leadership folks in our wastewater surveillance effort in the city of Chicago and across the state of Illinois. On the bottom, I have some of our very important lab folks who work in my lab. This is a big collaborative project that involves some folks at Discovery Partners Institute. I'm at UIC, Argonne National Lab Northwestern and then close partnerships with the city and state departments and public health as well as lots of other cooperating entities. So we have been working on this since 20, well end of 2020. We started in 2020 in Chicago and and then in 2021 expanded across the state. And so we have in Illinois across the state, we've done pilot programs in K through 12 schools. So I was really excited to know about Houston's work. We've spoken to Houston a lot when we were developing that pilot. And in Chicago, we have a couple of sub sewer sheds, so manhole sites across the city that were selected based on vulnerability indices. And then we have facilities we sample at Cook County Jail and O'Hare Airport. And so we have a couple of different institutional sites. And so super briefly, just to let you know and when we get to discussion, we can talk about this a little more if it's of interest to folks. But this is work that I was funded on from CDC to look at antimicrobial resistance. We call it SMART sewer based monitoring for antimicrobial resistance trends in healthcare facilities. And so this is a joint project with UIC and Rush funded by the CDC. And the idea is to develop wastewater methods that are specific to healthcare facilities. We do this really intensively in the first year. So we, the first year will be up this November. So in a couple of months, and really intensively sample at one healthcare facility and do a lot of experimentation with how sample they're collected, how they're transported, how they're extracted. And then with some limited point prevalence surveys that happen at the facility. And then going forward years two to four, it's to expand to additional facilities, do sampling slightly less frequently. And also a couple of the data with point prevalence surveys. So the hope is that at the end there'll be a really good descriptive method for how wastewater can be used in place of these really labor intensive and expensive clinical surveys and so the focus is on carbopenam, carbopenam resistance, and, and candid or is. But what, so it's been a little longer than I wanted to on that but the main part that I've been asked to talk about is the Sentinel surveillance at the airport and so this is work that we've been doing without here. And in in cooperation with the Chicago Department of Aviation so it's really nice about the work that we do in Chicago is we have a great working relationship with the city and the airport is run by a city agency and so pretty early in the pandemic. We approach them through the city and the plumbers there do a lot of the work for us and they are fantastic. And they've helped identify sites and so initially until 2022 we were sampling twice a week at two locations in the airport one that the plumbing staff and facilities folks that O'Hara had identified as targeting the domestic terminal and the domestic terminal and one that was exclusive to the international terminals, and we were sampling twice a week and what we found is that when we were reporting to the public health agencies, they were, they weren't particularly interested in the distinction between the domestic and international terminals and we'd end up lumping them together and talking about O'Hara in general and so in 2022 we really switched to capturing one site that the staff there had identified that captures the airport including ground crew and we only sample once a week. We run our assays on currently and starts to be to influenza and RSV, but we've been asked and done work with mpox when, when that was a larger concern here as, as has a Sentinel site. So, I just wanted to show this this is from a well over a year ago, two years ago maybe, but what we were initially doing was we would look at the trends in the PCR data and we'd like we would like we did with our, with a lot of our other wastewater data. We looked at changes over two weeks and changes over four weeks and and we'd report the trend whether cases were going up or down or likely to go up or likely to go down. And we found that at O'Hara it wasn't particularly informative to look at the trends like what what disease levels are or potential viral levels are at the airport because it's not the same group of people you're measuring and we don't, there's a lot of limitations to the to airport surveillance and and so just looking at trends didn't seem really as relevant at the airport as it would in in other sites so we now report just a risk level and because we're, we're, and so that we have different risk matrices that we use for different sites and and are calculated in different ways. But O'Hara is actually really simple where we just look at viral levels and we have threshold levels, like how much of the virus we were capturing and and it's reported 012 or 123 and 4 and and to be honest I think you know we report this weekly to the to the Chicago Chicago Department of Public Health. I don't know how I mean we're we're running the PTR so this is data that we get anyway, but it really what I think the strength is for the airport is on the sequencing side, and so this is this is also old data but I'll give you an example of what I think is the best use of the airport as a central site and that was when Omicron first emerged and so that's what this data is showing. At the time, it was not detected yet in first it wasn't detected in the US and then it wasn't detected in the state. And, although this airport surveillance is is under the purview of the Chicago Department of Public Health this state really thought that if anywhere would be the first site in the country or in the state to see Omicron, it would be at the airport. And so they just in a rush to identify Omicron, IEP really pushed to ramp up the sequencing there and so we collected additional samples more than twice a week and and sequenced tried to turn around the sequencing really quickly. We also ran PCR assays that were Omicron specific assays, and this was in in our early days of sequencing to so our sequence quality has improved tremendously in the time sense but what this plot shows that heavy black line that's labeled ripple. That's clinical data from from nasal swabs in the city of Chicago that the the rush university runs, and they were also on this mad hunt for Omicron and found. And so they were doing a lot of targeted sequencing like they find individual who was presenting with different symptoms or who had recent travel history and they were like get that person let sequence from that person. So they actually the first Omicron in Chicago is identified in those ripple samples, but what's what's plotted is how the proportion of the sequence data that's Omicron, and the greenish it's a little hard to distinguish, but the greenish lines are the O'Hare samples, and in fact, even before Omicron became abundant in the routine surveillance and clinical samples we saw it a lot in in O'Hare. And so I think this this was like a good use case for for this airport Sentinel surveillance but I think going forward. We've really been trying to push the sequencing as that the strength of the airport surveillance. And so this is just from last week and I took out all the data from the city of Chicago from from all our other samples, or the names, the data is there, but it took out their O'Hare. And so reading this across is so now we reported it with these heat maps of all the different lineages that we sequence. And so what we can do is, is see if there's lineages like you can follow this down. 1.16.6 and, and this one 1.5.10, which seemed to be more abundant in O'Hare. And, you know, this one is barely present or absent in in a lot of other locations in the city. And so that the tricky part about the airport to is that we don't. We're capturing travelers, but we're also capturing people who work there. And so I think this, this segues well into Aaron's work on aircraft sampling. But we're capturing, you know, anybody who goes through here, we're also capturing people who may be transferring so O'Hare is a major layover airport not everybody is getting out. And staying in Illinois, not everybody is getting out and staying in Chicago they might deplane and go elsewhere in the state so it's it's not really a signal for for the city of Chicago necessarily but it might give us ideas of things that that may be coming in and so I'll just wrap it up the last thing I want to say is it well to do the last thing I want to say one is that we're really interested in linking this genomics surveillance this is the the entire state. We're all in wastewater over all time that we've been doing this. And so we're really interested in linking the genomic surveillance that we do at the airport to community spread and at the city and state scales and understanding how predictive it is is it can we track movement of variants that we might detect in the airport. And then the very last thing I mentioned is that I think there's, you know, this, this discussion is centered around wastewater, of course, but I think environmental is really important and really useful at airports and other travel hubs train stations, you know, any, any sort of travel hubs and so we've we've started using air samplers to we have some air samplers deployed at the Cook County jail and we had a pilot where we were looking at air samples on on aircraft and possibly even at the airport anything together with with air samples and wastewater like a collective infectious disease surveillance from multiple environmental data sources can be really useful, especially for Sentinel sites. So I'm there. Thank you, Rachel. I think you've queued up Aaron perfectly by passing off from from airports and certainly the work on AMR is something I think we're going to want to discuss furthers very interested in that personally as well as for the committee. But let's go ahead and proceed to Aaron and then we'll have the most time for questions. If you want to, you can put it either in the chat or we can discuss it later too. Yeah. So yeah next I'd like to introduce Aaron Bivens from LSU is going to speak to us about airplane monitoring Aaron. Hi good morning. Thank you for having me. So I'm going to talk to you a bit about our work. Trying to use aircraft wastewater to surveil infectious agents. There we go. So of course, some of the earliest public health surveillance activity was associated with seaborne travel and travels always been associated with the movement of disease since the bubonic plagues. And of course our aircraft surveillance, our aircraft travel networks have far surpassed our seaborne ones at least in terms of moving humans. And so, when we think about the scale of this industry, prior to the onset of the COVID-19 pandemic they're about almost 4.7 billion people annually traveling via aircraft between different locations and then of course the pandemic kind of. Depressed those numbers but now the aircraft industry is seeing air travel industry is seeing a robust rebound and this is expected to only the number of people traveling by aircraft is expected to continue to rise. As a key characteristic of our globalized world. When we consider the scale of air travel this, this map is a depiction of all the long haul flights so flights greater than six hours. Linking the different continents and locations throughout the earth with flight times, you know, anywhere from 17 hours or less. And so really when we think about incubation times for infectious diseases. These are very efficient conduits for moving people and their associated microorganisms throughout the world and almost every continent. And so when we think about these aircraft, some of the features that are of interest are that one their closed system. So they're bounded we we board a number of passengers we have a manifest. And anyone who uses the bathroom on board an aircraft, their, their biological material is sequestered into the plumbing. And so the question that emerged was can we use data from aircraft wastewater to provide public health intelligence. So of course one of the first things we're confronted with is do, especially if we consider a fecal shed pathogen is do people actually defecate on planes. There's only only one study on this. This is self report data so I guess we have to probably hold it lightly but for short haul flights. Maybe around a 13% quote likelihood to defecate for long haul flights 36% which is certainly higher than I would have, I would have guessed. But there's certainly reasons to be skeptical about self report data from a survey, but that's kind of what we have for now. Now of course once someone defecates on board an aircraft. That material is sequestered into a waste tank. And so this aircraft wastewater actually for a couple reasons is an ideal surveillance matrix. First of all this these vacuum toilets I'm sure we've all heard them. They flush this fluid at somewhere close to 300 miles an hour because of the vacuum, the pressure differential between the inside and outside of the aircraft. So of course this material is pretty well mixed by the time it reaches the waste storage tank. And then for fuel efficiency we don't want to transport a lot of water so usually it's highly concentrated with 200 to 300 mils of fluid per toilet flush. And so of course a highly concentrated matrix could be good for trying to detect something that's rare, assuming we can overcome analytical difficulties like inhibition. Now, once these aircraft land, of course they need to be serviced so all that waste that we've sequestered in the tanks needs to be pumped out and reset for the next flight and it turns out that this is actually an opportune moment to collect a wastewater sample. Not what I'm told is not every flight is serviced necessarily but my guess is most long haul flights are serviced. And so there have been a couple devices invented that connect to the aircraft here, and we're able to siphon off some of this wastewater as it's being pumped out of the aircraft. The collection logistics are have to be carefully coordinated of course these ramp areas are restricted areas and they're restricted to authorized personnel. The only people that are authorized to touch the aircraft are the ground handlers. And so we need to coordinate with the airlines the airport authorities terminal operators and ground service ground servicing companies for these efforts. And I think that's actually potentially one of the strengths here is that really to do this you you have to have the government public health agency in in the front leading the effort. It's really hard to negotiate all these things in the absence of a public health agency on the team and leading the effort that's been the case here in the US. So I think that's a strength of this approach. This idea really isn't a new idea. One of the first studies, at least in terms of public health surveillance is from 2015. A team in Denmark did some shotgun sequencing of wastewater from 18 flights for antibiotic resistance genes. And they propose this as a as a new paradigm for pathogen surveillance in their paper in 2015. We saw another study in Germany in 2019 again ARGs 2019 also in Denmark looking at virus community composition in aircraft wastewater. And what's interesting is in in in this study in Germany when we consider the, this is the number of drug resistance exhibited by the isolate so this these isolates are resistant to three different antibiotic compounds. And we see that aircraft exert displayed a unique signal relative to the municipal treatment plant and then the miss municipal treatment plants without receiving any effluent from airport terminals. So we see a unique signal here. Same thing in 2019 when we look at the viral community and flights originating from South Asia versus North Asia and North America. We see unique geographically associated signal in these samples. So with the onset of the COVID-19 pandemic. The idea was, you know, can we look for SARS code to RNA and these aircraft wastewater samples so we began with just a very small end of three. We tried a couple different concentration methods, five different assays, and we were able to detect SARS code to RNA, although it was at very low concentrations 400 to 300 gene copies. Probably one of the more interesting observations here too is that we did some we seeded some of the disinfectant blue juice with this RNA and we were found that the signal was persistent out to 48 hours which we considered like a reasonable handling time for aircraft wastewater. In a follow on study to that we took collected wastewater from 37 international repatriation flights into Australia. These are about 6500 passengers. At that time, Australia had a mandatory quarantine. So all these passengers went into quarantine. During that time there were 112 incident COVID-19 cases among these passengers. And we found that the aircraft wastewater was actually predictive for 84% of these incident cases during quarantine, which is I considered pretty pretty promising. There's a couple other interesting observations from this study I want to point out. First rinse eight samples so we in 28. In 28 cases. We were able to collect a rinse eight after the tank was serviced and in two of those samples they were positive for SARS code to RNA, although it was at much lower concentration than our. Hot samples, but it's clear that we're probably going to need some sort of cut off values for this. Another really interesting observation to me is that we had eight aircraft with only a single COVID-19 case on board, and for six of these eight, the wastewater samples were positive. So that's 75% positivity compared to a 30% 36% likelihood to defecate from from Jones et al which I think is suggestive. I think about this is like a Bernoulli trial, given a probability of 36% for someone to defecate the probability of observing six of eight flights positive is about 2.5%. So this is a low probability of event that we had during this study. In another study we were able to detect an Omicron infection so there were 12 flights arriving to Australia one of them was arriving from Johannesburg. We were testing screening with RT QPCR and we found actually a sample with the deletion 6970 which is a signature of Omicron. We took that sample and sequenced it with two different protocols and ultimately we were able to detect 63 of the 72 defining mutations for Omicron. And turns out there was a passenger on board this flight infected with Omicron variant. And interesting is this flight landed in Darwin the same day that Omicron was declared a variant of concern by the WHO. So it kind of demonstrates just how how quickly and efficiently these microorganisms are able to diffuse via these travel networks. They were replicated elsewhere so Dubai close to 200 flights France, interestingly in France there were two flights that arrived and were positive had positive wastewater results. And then they were actually able they used a rapid screen and then they were actually able to test the passengers and found 20% positivity for Omicron VA one, and the sequencing of the wastewater and the passenger samples aligned fairly well. Today more recently had 93% positivity among 32 flights. And here in the US at JFK 81% positivity and then of those samples 32% yielded Omicron sub lineage genomes. And these genomes tend to tended to agree fairly well with what we know was happening in the countries of origin at that time. We're looking for some other microorganisms including pathogens. We've done a small pilot study with just 24 samples and we've been able to find you know crass phase of course human polyoma rhino virus A and B norovirus influenza. So you can see there's a variety of infectious agents we've been able to detect in these samples. A few things that we were were non detect, but overall promising results. We did a bit of modeling, just a very simple Monte Carlo model to estimate how many flights would we need to sample if we wanted to collect material from roughly 10% of all international arriving passengers. And we consider two scenarios one, let's assume there's only shedding by the fecal route to let's consider the possibility that some of this material is actually in urine. Our participation rate in this model is about 36% of passengers and here it's 75 to 100% and you can see that across the 10 airports that receive the most international arrivals. We would need to sample anywhere from 200 to 40 flights per week for a fecal shed pathogen or 60 to roughly 20 per week in the case of a urine shed pathogen, mainly because those participation rates are so different in the sample. Of course that's like a general purpose bio radar as it's being described there's also the possibility that you could couple this approach with some network modeling in order to target specific nodes in the air transport network. This could be done for like a general purpose surveillance system or we could actually in response to the emergence of outbreaks. Use these network models. This is gleam biz, which is a web based application. And based on the characteristics of the disease, we could actually target some nodes. The other thing we could consider is places where there's not as much clinical surveillance. Of course, we can design the aircraft wastewater surveillance system to maybe provide better coverage from those areas. There's a lot of important questions that are still outstanding probably more questions and answers how many passengers actually contribute to this sample. The residual contamination in the waste tanks is certainly you know our sample size there is still only 28. What other analytical techniques could we apply so you think about if our interest is primarily sequencing. One thing we could do is screen with a rapid method such as an RT lamp and then use that to to screen our samples and get them into sequencing faster. There's always the question of what other pathogens. How do we interpret and apply the data in real time and then how do we integrate into public health decision making I think Dr Friedman is speaking later and can probably add some more here. A couple of key takeaways from my experience so far with aircraft wastewater surveillance is that the data can provide geographically resolved insights. SARS code to can be readily detected and sequenced from aircraft wastewater and we've had pretty pretty good success detecting some other pathogens as well. Importantly, the aircraft wastewater signal does seem to be predictive of incident COVID-19 among passengers. Which means that if you imagine some future pandemic, you could potentially notify passengers and advise them to seek testing based on your aircraft wastewater results. Yeah, I'm going to I'm going to leave it off here. Thank you for your attention and I'm happy to take any questions. Super. Thank you. Thank you, Aaron and thank all of our speakers. Let's go ahead and open it up to questions and I'd like to start with the committee. Because they have to write the report so give them preference in asking questions. Go ahead and raise your hand hopefully I can see those if not Stephanie. If you can see them call them out to Chuck is raised to sand. Yeah, just a question on the Houston school data. So, I don't know what the Houston school district is like is there a lot of student transportation from different zip codes to the zip code of the school. All right, I'm just trying to get my mic work. Yeah. I, I think that definitely does occur. I'm not sure how much it occurs at these specific schools. So I'd have to look into that. I don't have Lauren Hopkins is on here. I don't know the answer to this but I think it's very school dependent in terms of the amount of transportation that's happening at a specific school and how many people are coming from outside zip codes. I mean looking looking at the temporal correlations of adjacent schools I think it would be fascinating and I think I'd strongly encourage you to try to get your arms around that data. Yes, I think that's a great suggestion. I think. I'm hopeful it's you will yield something interesting I think in general we do see like a lot of sample variability for these facility level samples that make some of these correlations really challenging to establish. And so, well, I'm hopeful we'll get something from that. I don't know if other folks this is about the silly little sampling but in general we see, you know, a lot of sample variability, much, much more at the facility level than we'll see it. That's a great plan. All right, Scott. Thank you. Sorry. I had a question for both Aaron and Rachel. And it's this idea that because the populations in the airports are so transitory. You've already kind of indicated that following trends is an issue. I'm curious just to what even the risk levels, what value they have, and how broad a geographic area you think should be responsive to that risk level. And then kind of couple that with a question regarding the timing of these analyses. The idea of sampling every flight as it comes in, if we can get the results by the time that people leave that's great but you know the dollars for public health follow up on every passenger is, it's significant. So just from a utility standpoint, how does that reconcile what you're thinking. I think it's more about seeing at least I'll speak for the airport surveillance. I think it's more about spotting something there before it's it's seen elsewhere and so it's not even like risk level so much as like alerting. I don't think if it's used right which at this, at the moment I don't think it's used to its potential in in Chicago, or in the state but I think, ideally, it would, it could trigger you know we see some a new, whether it's a new stars Kobe to variant or a new, a new pathogen or something that's just not seen elsewhere, we can alert trigger some sort of action to, to keep an eye out for it elsewhere. And so the response to, to detecting things like MPOX is, you know, heads up to clinicians if somebody presents with nasty rash, you know, don't don't write it off as eczema there's MPOX was detected. I don't, I don't view it so much as a risk but as a way to inform what's there, which I think was was being used for even the passenger the traveler surveillance program that the CDC runs sequencing individuals at airports, just giving a sense of what's, what's there and what could be coming from elsewhere. So just as follow up, are you then looking for NEPA right now. Am I looking for what now. NEPA. Thanks for your response in the chat. Yeah, I think I just responded to Chuck about the CSTR. I think yeah, a lot of this depends on how quickly we're able to produce the results. And then of course, I guess I think of like don't let good be the enemy of perfect or don't like I can't remember the saying but you get what I mean if we can if we can interrupt some of these transmission chains. That would be helpful so in my mind right you have this manifest of people you know who was on the flight you have their contact information. In the event of maybe for like the flu or something it's not as useful but for a for a pandemic especially early onset. You could potentially follow up and encourage people to seek testing or to maybe consider quarantining themselves. So I do think there are some direct actions you can take. Of course, with all surveillance systems right the more rare. This event is the harder it's going to be to detect especially when you're trying to be resource efficient in your screening. So, there's just a lot of tension between between these two purposes. So, thank you. Mark, did you want to respond to that too. Yeah, I mean I think. I think it's basically kind of expanding a little bit on on where Aaron was finishing up which is I perfect I can really agree the perfect should not be the enemy of the good. We all you can. How are you. Yep, I got yep. No, don't worry. That's my students all the time. What are the other piece to that is what are the levers that you even have control over like what are your levers of control and so if you don't have levers of control it's data for the sake of data. If you do have levers of control then you have data that's useful for figuring out which lever pool or what combination of the pool things like that now. Like collecting the data to be able to say what levers do we need to envision we need to have in place. That's not a really interesting. Interesting approach. I think. Again, if you can narrow down those time frames to be able to get from sample to result. And you already have those algorithms in place to be able to run the computation. I think you're at that next stage of trying to prevent the next pandemic. I think one question I'm kind of wrestling with in all of this is like, can we pull and will we pull are two different things. And there's a lot of beyond the science. There's a lot of forces at play in how this data get used. And that's the part that for me. It's kind of hard to know, right, like how confident you need to need to be. How much research do you need to have the confidence to like have confidence that if you pull the lever you're not doing, you know, you're making a good decision. I think that depends on the size of the lever. I know if it's if it's if you're going to like in your case. Is there a lever is there ever going to be a lever where you shut down Shaldeghal airport because of what you found on X number of flights. If that lever is ever going to exist that needs that needs a lot. In order to pull that if it's now going to be smaller order like it's like the stages that we go through for ODRC some of those initial stages are almost nothing. The offenders don't even notice that they're happening. But they're there. You know the correctional officers are so used to it at this point that they don't even really notice it which has an opposite danger. The more routine something gets more likely you're making error during it. Alright, so, again, you got balance all these things but I think it really comes down to is how big is that lever that you're going to pull and then that tells you a little bit more about weight of evidence. Thank you. My question is already been answered, but I have a question for Rachel. Can you share some more detail about your sampling strategy. Like how did you determine the frequency of sampling at the airport. I realized that took me a second. I was actually going to say something on that to the to the last question and Scott's point about sampling frequent. I think sampling frequency is is kind of critical and at least in interpreting the data because like, like you all said you're not going to sample every single flight and we're going to sample, you know, every, every day, like we're resource everybody's resource limited right and so what I think it's an important question what amount of what frequency is useful and what, what kind of assumptions or uncertainties are there, given a certain sampling frequency so something's very low abundance and there was a passenger on one flight. That was not the one that you sampled or it came through the airport the day before you sampled, you're not going to catch that. So, you know, I think it's a long winded way of saying, you know, we came up on for stars Kobe to one week sampling once a week was sufficient for getting a picture of what what COVID variants were present. But is it the right frequency for other pathogens is it the right frequency for, you know, if you wanted to do risk level or anything like that. I don't know but for to get a picture of, of variants, and at the rate that we turn over data. We would get another sample, a week later, if we missed it the first week and and so that's how we came up on that, both resources and our goal. Sandra. Yeah, I have a question about the active kind of auto samplers versus the passive sampling and I know Rachel you're actively working on that and mark you mentioned it. In this report we're going to try and address a lot about trade offs and cost versus the quality of the data I'm sure is going to be a common theme. Do you have any sense on where the passive sampling is going to benchmark against what I would think is more the gold standard the auto samplers or one will know that answer is that a year out six months out. There's so much on the target to and there's so many trade offs like with one method, our samples are dirtier and with one method, and actually, right now, I didn't say this but right now we're doing grab samples at the airport which is like, not the ideal sampling but the plumbers at the oh hair plumbers are the ones who are collecting the samples for us, and we gave them auto samplers and they didn't want to fuss with they we tried it we place them. They wanted to charge the battery and they bring up thing and they were like this is this. No, and because they're, they're volunteering and they're doing this, they're doing a favor for us. We compromised. You know, not just like the gold standard for for the type of sample you get, but depending on who sampling Lauren was mentioning who samples for the school projects and, and I think you all are very lucky that your health department has has hired people to do that but it really depends on the site and and the sampling and what they're willing to do for you. So that that needs to be a consideration to sometimes the best method for for data isn't the best for logistics. So, so one of the other pieces is a couple of the pieces to that one is a lot of the, a lot of the methods that are like decision analysis models or risk models that these that these data are streaming into our expecting quantitative data and the passive samplers will give you effectively present absence of the ones that I have familiarity with so you can still run that through and you can still get a quantitative result from it, but it would be. It is a little bit more challenging. The other piece to that is that that's not all for for loss as well. So if you do move over to something that gives you some get gives you results that are more aligned with presence absence. Then there's a threshold at which the presence absence occur so you can do. You can do methods along those lines so you know we're working on something similar and food safety right now with presence absence data where it's it's not it's not the best but it would still be something that you can use, and you can look to see how frequently you get a different basis where we're looking right now with regards to using the passive samplers is the frequency of hits so you can actually get more of those into the system along the sewer line depending on where your access points are so you can actually look at the so you look you can look to see whether or not dispersion is really that big of a problem depending on the size of your sewer so if you're monitoring something that's going into a very large sewer pipe. You might need to account for dispersion or uptake into bio solids or something else where you're losing the signal along the way and passive samplers look like they might be able to do do pretty well with that to get a better idea of how complex the consideration need to be with regards to that so there's some really interesting questions of the the passives can can get at the other aspect of it is that once we can build up the computational methods to be able to use those just as effectively as the auto samplers because they are so much much epically cheaper and easier to place and you don't have to worry about battery and you don't have to worry about cooling and you don't have to worry about all these different things. There will be a lot better by way of where we can get them spread out into different communities how we can do targeted sampling and then go from there the the thing that I would come back and remind about is that expansion if we're going to go down that expansion route at all then again it would it needs to kind of come back to what do we know about the community what's the effect size that we're trying to monitor for and properly power it so that we're getting representative samples for whatever group it is that we're monitoring. We've been using some passive samplers here we have a lot of rural treatment plants in Louisiana that have no resources. If you do the math in the national wastewater surveillance system if you're served by a small treatment plant you're about 12 times less likely to be included in the system. So we've been chunking in some passive samplers with activated carbon on the hunt for some different pathogens and they've been extremely easy for us to deploy. We're also experimenting with waste surface waters that are receiving on site sewage system effluent as a way of like hey can we look in surface waters. And see any trends there for these people that are on decentralized sewers so I think passive sampling is really promising. A lot of questions still to be answered. All right Scott last question before break. Sorry, struggling with unmute for some reason. Mine goes to that question passive sampling so are you're you currently using passive samplers as just plus minus benchmarking them based on the time deployed or have you actually done the source isotherms and if so are you doing our source isotherms in the different water systems to understand the matrix effect. We use them we use them passive samplers across the city. But Aaron's done a lot of work or some work on on calculating the dynamics of passive samplers and I think it depends on the material and the flow and that has to be benchmarked for every unique site or that but our logic is if we're doing it at the same place that it that it's there's consistency. There so we could compare those samples to to the same sample to different samples from the same site. But you haven't validated the recoveries or our benchmarking against time. I mean we've looked at recoveries but not we haven't done the experimentation I think that tastes like lab scale reactors to look at flow and absorption and and things like that and that that we haven't done. But I think actually with the antimicrobial resistance project that we're doing at the facility. We're going to have clinical really tight clinical data to line that up to and we're doing we're taking. We have an auto sampler on site we're taking grab samples and we're doing passive sampling and we have the point prevalence surveys and other data. So I think in that for that location will be able to to get some some good answers on on benchmarking. We're kind of treating them as like a TSS sampler. So what I'm trying to do right now in the lab is characterize TSS isotherms and kinetics. And we'll see it's you know we're learning a lot of hard lessons right now we just started these experiments and it's like there's a lot more than I would have guessed involved. All right. Thank you I want to thank all our speakers again. Obviously welcome in and would be great if you could join us for the second part because we're going to be addressing some of these same issues, if your schedules will permit. We're going to take a break until a quarter till, and then we will reconvene. All right, welcome back everyone. I think we need to put up our slides again. I think our, our next speaker we're delighted to have Cindy Friedman with us from the CDC who's going to talk about kind of following on the theme of this morning. Airport monitoring plans from a CDC perspective. So Cindy if you're ready. Yeah, I'm here I can share my slides if you're ready. Can you hear me okay. I can perfectly. Okay, great. Let me just get the screen to up. To share and let me make this. Okay, are you seeing the full slide. Yes, perfect. Okay. Okay, great. So thanks for inviting me to talk to you. Oh, I just have some pop up here one second. Okay, there we go. And today I'm going to talk to you about multimodal surveillance in the global transportation network, specifically CDC's traveler based genomic surveillance program or TGS. I, let's just get started. You asked me two questions today. What is the current status and plans for airport monitoring of infectious diseases and how does airport monitoring fit into news. And the broader CDC strategy for detecting and managing the spread of emerging infectious diseases and hopefully when I finish today, we'll have answered those questions, but I'm happy to take any additional questions. And I have about 15 slides. So I'll just start off with the traveler based genomic surveillance platform, which plays an important role in US national bio surveillance. The program was started back in September 2021 as a proof of concept project. It's a public private partnership with ginkgo bio works and express check and basically we partnered with an air airline spa airport spa group who was doing testing for outgoing passengers they converted their spa company because of the pandemic into a company and we heard them give a talk and thought, could we partner with them because we were sort of behind on every variant that was coming into the country when alpha emerged when some of the other ones emerged and this was at around the time of delta. And so we put together a program. And we didn't know if it was going to work, but it was operating at the time in three airports, and it was testing volunteer international travelers by having them self collect nasal swabs at the airport, anonymously. And answer a few demographic and clinical questions and the pilot was a success we enrolled, we have enrolled over 323,000 volunteer travelers. We're currently at six airports we've been at seven we've been at four right now we were at six. And during the last year about a year ago or more we thought that you know how long or travelers going to continue to volunteer to give us a sample they don't get anything in return except a free take home antigen test and at times that's been really valuable when test supplies were limited. Most people say they participate because they want to do something and feel like they're helping the community and public health. But we didn't know if that was going to last and we wanted to look at other avenues to potentially get the similar data from arriving international travelers and travelers are good because they get and spread infectious diseases quickly and give us a clue as to what's happening across the globe. So we started a pilot, and we've continued that pilot into a program of collecting airport and aircraft wastewater samples and I'll go into the details of that. And that's obviously the focus of my talk today. Just some other information about the program it has two goals. They're enhance early detection of new variants and also we've been able to really fill gaps in global surveillance, especially recently, where we're seeing a 90% decline in testing and sequencing globally we've really been able to fill in those gaps using the traveler as a sentinel. And the other big piece of valuable information is that our results are reported within eight to 10 days of collection so pretty near real time and and quick. We reached travelers on many flights from over 135 countries, and we've been one of the top three contributors to get saved for us submissions for the last several months. And so, I'll just review the three parts of the program so I've just told you a little bit about the traveler nasal sampling program which we're not going to talk about today. And then that we started the airplane wastewater sampling program last summer and 22 as a pilot and then expanded to broader implementation. And I'll go into the details but wastewater is collected as part of routine lavatory servicing of aircraft on arrival, using a custom made collection device. And we, if this provides samples without direct traveler involvement. And we can still get the country of origin of the flight and then more recently we've started looking at airport Triterator drain sampling as another modality in our program. We're, and I'll go into some of that as later on. So I think I'm probably peep preaching to the choir already I don't know I sorry I missed this morning session but I had another talk and I just got back at noon so I caught the last little bit. But just in case I'll just review quickly we go from more granular information when we sample directly from the aircraft when it arrives at the airport. The next step would be the lavatory truck that drains the sand, the wastewater from the plane, which then dumps their way, the waste in a Triterator different airports have different numbers of Triterator some are lucky enough to have like an international only Triterator and a domestic Triterator. And then there's the terminal and then the wastewater treatment plants we go from more granular to less. So let's start with the aircraft piece. And this is our workflow for the samples are collected. At the, at the airplane, they're sent to the lab for PCR positives are sequenced and then the samples are tested and sequenced and results are available within eight days. For the pilot. This is a picture of the device the collection device which is an end to end collection system that attaches to the both the plane and the hose that attaches to the plane so the this yellow pit, it would attach to the plane the hose would attach here. And oh I'm not showing you the yellow bit, the hose would attach here and then this is our sample collection bottle, which is a half a liter with a spigot and so there's usually three or four tanks on a plane, and we get a sample from each of the tanks we think that there's good mixing because of the turbulence during the flight so that there's not an issue that the sample isn't well mixed. There's a version of this or this device being developed by Ginkgo that doesn't involve unscrewing the bottle that really is really a seamless sort of like vena puncture type device. And so for this pilot last summer at JFK we successfully collected wastewater from 88 flights. There was no disruption to the ground handlers there were no accidents. There were no really no issues it adds like less than five minutes to operations probably about three. We detected SARS CoV two and 65 out of 80 samples that, and we, those were tested positive by PCR so 81%. We were able to identify genomes in about 40%. And these were consistent so we've selected flights from three countries, Netherlands, France and I believe it was the UK and the secret the genomes that we identified were uploaded to kiss aid and at the time the circulating variant in Europe was BA five and 90% of our lineages were BA five so we were finding what was out there. So this was a eight week pilot. Then we decided to take a look at wastewater sampling at the Triterator level at the airport. Because one of the challenges which I'll go into a little bit later is getting airlines to agree to allow their waste to be sampled so you need to have the airlines on board then you need to train the ground handlers and work with them not every airline uses the same ground handling company there are many of them and many different permutations at different airports so you know an airline could use one ground handler at Dulles airport and a different ground handler at San Francisco so a lot of moving parts and then the airport has to be also on board. So with the Triterator I heard you guys talking about auto samplers we there's the Triterator dream we started in San Francisco this spring. And this is the Triterator on the top and the, the auto sampler is over here that the hose from the lav truck attaches and then the sample it's triggered by flow and we get a daily sample from the Triterator. In San Francisco they have an international Triterator. So mostly it's international flights, but occasionally a domestic flight could be put on the, on the side of the airport where that Triterator is and so there could be mixing. And so you don't get that level of specificity of knowing which flight you're getting a result from. So this is where we are in the current collections. We have the aircraft wastewater. Most recently we've collected that since the spring about 126 samples with it again in 81% positivity. We had consistently about 4043% return lineages. The interesting piece here is that 73% of those aircraft wastewater samples only yield one lineage. And these are some of the lineages we've found which are the current circulating lineages. And the Triterator with, you know, high positivity there but actually we get many lineages detected so whereas we got 73% with one lineage we only get about 10% with one lineage we get 90% and multiple lineages detected. And that makes sense, you know, it's a lot of different airplanes dumping into this sample. And these are the lineages that we have found. There are limitations of both aircraft wastewater and traveler based surveillance and that makes them really complimentary approaches at this point in time. We don't think that one could supplant the other right now. For the traveler side not all travelers participate it's a voluntary program. If we had more hubs and international airports that would help improve the scope of the program because we want to get a broad depth of coverage so Africa, Asia, all the different parts of the globe places where people aren't reporting what variance. They're seeing or even testing or sequencing. And then sampling in individual travelers can be more resource intensive we use a pooled sampling approach so we group them in pools of 10. And so if the pool is negative the, we don't test any further but if the pool is positive then we go on and sequence test and sequence each individual on the pool so that helps to fray some of the cost. On the wastewater side. I think you're all familiar with the, there's a paper by Davey Jones from the UK and not all travelers use a laboratory on flights and he did a study looking at this, showing that the chance of defecation was about 36% on long haul flights over six hours. And that's the other piece you really need to do this on longer flights short flights aren't going to yield as much. Travelers originate in the place where the flight originated so you can have a traveler coming from the South Asia going through London Heathrow and then to JFK. So when we're getting the sample from that Heathrow JFK flight, we're getting waste but we think it's from London but it could be half of the plane came from South Asia so we, we lose that granularity that we get from the traveler and the reason we get more data from the traveler is because we asked them, they fill out a short questionnaire about where they got out of bed in the morning where they've traveled in the last 10 days. The potential for residual virus in the lavatory tanks we've done some initial studies looking at after the tanks have been drained with and rinse with glycol and we haven't seen a significant amount of virus in there. And we've also are doing some work with partners in the UK to look at round trip flights so the same plane when it goes from, say, Dallas to Heathrow and back you can look at what you are finding in the on the waste water on each side and they shouldn't be the same if the if it was sufficiently cleaned. So what are our current focus areas and future plans we're enrolling new airlines, as we speak where we have several that are set to join this month this has been the most challenging piece I think for me, convincing the airlines to let us do this so we're not really excited that we have new partners coming on board. We're expanding the sampling source we're probably be adding more Triterators at different airports at additional US airports. We're initiating multi pathogen detection and we're doing this in alignment with the way news is doing their multi pathogen detection. And we're specifically including many respiratory pathogens but the three of interest for the fall respiratory season or SARS CoV to flu AMB and RSV. And we're also building these global partnerships I mentioned the UK we're partnering with UK HSA and New Zealand, and several other partners to do these global projects where we collect airplane wastewater on both sides of a route data. And I think this is a good model for the global community at large. So this is some of the multi pathogen work we're doing we're using several platforms. And they're underway for the multiplex we're using multiplex QPCR for both the nasal samples that we get. We get about 6500 nasal samples a week and the wastewater samples. We're doing target enrichment sequencing. And we're working with the subete lab at the bro to use the Carmen platform targeting several viruses. And where is the program going so I just, I think one of the interesting pieces is that this is really a platform the traveler is genomic surveillance platform so and it can be built upon in three areas in the mode of sampling in the pathogens that we're sampling and even as the MR genes and the global network piece so we're starting to pilot air sampling in in a few of our airports and sequencing from the air samplers. We're partnering with the University of Wisconsin for that pilot. We're enhancing surveillance capacity for global migration events. We've put questions on our questionnaires on the traveler side, but we can see this platform being used for mass migration and mass gatherings as a way to for early detection. We're collaborating with the EU and other partners to try to establish a global network for airplane wastewater surveillance so aligning methods data sharing so that data can be triangulated and compared there's some modeling work done by the best and Yanni group at northeastern that has looked at you know the having several key transportation nodes doing airplane wastewater surveillance can really increase the time to detection of an outbreak that starts at one part of the world. So we're looking at that there's several groups interested in that. And so I wanted to get to the, the second question I think, how do we fit in with news and CDC larger objectives and TGS and news really have complimentary objectives for advancing environmental surveillance. For us traveler service sentinels for early detection and introduction of pathogens to the US so we're really getting a picture of what's going on globally by using the traveler as like a FedEx package bringing the sample to the US. And that's important because, you know, getting the samples here can we can send them to the lab for further characterization so if there's a new variance that we detect in a sample, we can get that to the lab and it can buy critical time if you have to wait for another country to send you a sample. And so in many cases we've picked up variants ahead of other community indicators and I didn't bring all the data with me to this talk. A lot of it's from the nasal sampling program. And which we also fill in gaps in global surveillance. And that's increasingly important when clinical testing and sequencing data are unavailable and this complements news. Domestic focus. And we can sometimes even inform them on what to look for so if we're picking up a variant overseas that can help direct news to look for that variant in community wastewater. We leverage multiple surveillance modalities and it can vary over time so we can scale up scale back we're pretty nimble and and depending on what the situation is, you know, some viruses are not, you know, flu virus a segmented is not the best to look for stereotypes and wastewater you need the clinical sample we did a pilot with the flu group last year, and we could detect flu from self collected nasal swabs from asymptomatic travelers, and they were able to culture it in the lab. And then aircraft wastewater testing is cost effective. It's a cost effective way to attain obtain the biological samples in an anonymous way but still preserving some key information, not as much as you get from the individual traveler. So we're coordinating on surveillance priorities. And as I said we detect new and emerging variants which can inform news targeting efforts for what they're looking for in terms of variants and sequences and we're aligning aligning with them on lab methods and multi pathogen targets and panels. We definitely have plans for future collaborations to better understand the transmission from the US port of entry into the community. So looking at the data from the airline, the airplane to the airport to the community would, I think would be very valuable. And then again the complimentary work we're doing with global partners in the transportation network for early warning system and I think I've mentioned some of these unique considerations for aircraft wastewater there's the logistics of sampling access to collect the samples, the need for specialized sampling equipment, you know we've talked to some other countries that are doing this and the methods vary from scooping poop out of a drain to like opening the hose on the lab truck and and those are less than ideal it's it's really nice to have a close system to collect the sample. The partners as I mentioned requires buy in and acceptance from a lot of non public health partners. And it requires a lot of coordination and data sharing to really make this work on a global level. So, that's all I have for today. I happy to take your questions just want to acknowledge all the folks that work on this from the three groups, and we have some resources here. Thank you Cindy that that was great. I actually participated I was one of the people who gave a sample at all one time they did they asked me where I woke up that morning which was Nairobi so glad to be one of the 300,000 or whatever. Thank you. I have a burning question but I'll put it off because we want to hear from from David Percy first on really one of the key questions which is how does he use institutional data for public health decision making and then we'll have open it up and and have sufficient time for questions for for all of the panelists so thank you. I'll stop sharing. Yep, and David I'll turn it over to you. Okay, so can you hear me okay. Perfectly. All right terrific so first of all I want to thank the academies for inviting me today it's an honor to speak. I also want to thank the presenters earlier today for really great presentations. I also want to especially thank them because they've already discussed about half the things I was going to bring up but Nevertheless, we'll move forward. So I don't have any slides I'm just going to talk as a local health authority that you know the physician in the health department who did a lot of our public messaging and I can't talk about institutional and sentinel sites which is the, you know the focus of today's discussion without talking about the, you know, when we talk about the community wastewater sampling and you know the measurements that went on a community level and the reason for that is that we had to educate is this was a new tool to be used in public health. And of course the pandemic brought a lot of attention to public health. And so this was an opportunity for us to educate the public about what our mission is because I think that you know to some degree to public health credit. We were kind of off the radar for most people which is really awful, but certainly aren't anymore, but it was an opportunity to educate folks and so we had to build credibility and I won't get into the discussion about how this all became very politicized but we know how that became very very difficult to operate as people who are looking out for the greater health of the benefit of the greater population. When all the politics got involved so credibility was incredibly important that we build credibility and so in Houston I will say that as Dr Hopkins and Dr Stather's group embarked upon this wastewater monitoring the, you know, I became very excited because I could sort of foresee some of the problems that we were going to have although I will also point out I think all of us had the same experience that COVID clearly didn't play by the rules if you will at every turn COVID surprise us with what it could do, and made, you know, I now have a mantra that says if you want to make a mistake in public health make a prediction. And so anyways with that being the case we needed credibility and so is the wastewater sampling and the monitoring progressed and became very very accurate we learned a couple of things that we use across the community that was as well the first problem we had was that you know the units of measure. So, in Houston we chose July the six 2020 which is the peak of the first wave. And on that date we had no idea what was going to come in the future but we just picked that as a 100% value because the units of measure were, you know, 1.4 times 10 to the six, you know, Byron's per cubic million or whatever, whatever the, it was which means absolutely anyone other than people like Dr. Stadler. So we couldn't use that so we chose that as 100% value and we had to educate the public on what that meant and then as we move forward, the, you know, the virus changed a little bit right and again it became difficult because what we started telling people is, you no longer need to pay attention to what the number is, but rather which direction the number is changing. So that became important but the bottom line was is we learned that what happened in the wastewater accurately reliably predicted what was going to happen to the positivity rate across the community, and that reliably predicted what was going to happen with the hospitalizations in our local hospital community, and it was reliable and happened time after time after time suddenly everybody in the community became focused on what's the wastewater I got many many calls about you know what's the wastewater doing. And you know who would have thought three four five years ago that anybody would have pardon the pun but who would have given a crap about what was going on in the wastewater. But suddenly, you know reporters are calling I got Congress members calling I've got council members calling I've got all kinds of people wanting to know what's going on in the wastewater. So I think that was really important to public health globally for us to become that source of information which reliably predicted what was going to happen to you know really across the community. Once we had that and we started looking at institutional and Sentinel sites in particular places like jails. And in Houston, we've got all kinds of jails and if you're in a big city you probably again it's like most people think that okay they're you know the county or the city has a jail. And I will tell you I've learned so much about jail operations, and it is a completely different world than what I thought it was and I suspect that you think it is and, and Dr we're from Ohio State. You know, thank you for your presentation but jails are incredibly complex places, especially large jails and here in the city of Houston we are within Harris County and the sheriff's office operates our big jail here it's got a population of 10,000 people. And we were, you know, we were fortunate that all the drainage from that that large jail did come to one place outside the jail where we were able to sample the wastewater and of course there was a lot of virus circulating in the wastewater and we work very closely with the medical staff in there. And they developed a program where they were they started basically quarantining the new admissions and observing them for you know, as many days they could it was generally around seven to 10 days it wasn't the full two week the full working day incubation period they just couldn't do that but they were able to you know, quarantine them for a sufficient amount of time that when people became symptomatic, they would, and they were doing testing of new admissions, and we were able to keep the, the, the amount of COVID spreading within the jail at a remarkably low level and here we are now three years later. And you can imagine a, you know, after all those years, we had eight deaths within the jail, only eight.  They got them in in there but it's not, it's not just young healthy men it's a quite varied population of people it's predominantly male, but their health status is all over the map. And even some of the young folks have got some pretty serious health problems because they don't live a healthy lifestyle, but we were able to keep that down to only eight deaths here three years later. We also looked a lot at the schools and we've talked a lot about schools but in addition we looked at nursing homes and other high risk population of people and tested individual nursing homes. And so we were able to go in we got very aggressive here in Houston we got very aggressive going into the nursing homes. We've got around somewhere between 250 and 300 nursing homes, and the health department partnered with the fire department to go in there and one little thing about that the reason we partnered with the fire department is when the health department shows up at a nursing home, they all panic.  When the fire department comes, oh it's the firemen again because I'm also the EMS director here in the city of Houston.  And so quite honestly the nurses that work in the nursing home know the firefighters that generally come when they call 911 for a seriously old nursing home patient so there's a relationship there. And we showed up with the health department folks who they didn't know, but with a friendly face of firefighter who they did know, we got let in and we were able to go through and we did a lot of proactive stuff. Early on, and then we did a lot of reactive stuff if you will later on as we saw a nurse comes that came to again it was a trust issue in the wastewater and the reliability and the accuracy of the wastewater values became that currency that we were able to to bank on. And we're going to the nurse homes and let them know and again we were able to teach them how to do things so here we are. You know years there at one point there is a statistic I think the CDC put it out that about 40% of all deaths, COVID deaths in America were coming from nursing homes at one point it was in November of 21 I think. And at that point in Houston, we had about 15% of our deaths were coming from nursing homes. And now here we are years later and nursing homes I think across the nation have done better. There are other parts but anyways at the end of the day, I can remember there are only eight deaths in the Harris County jail because it's also is only 8% of our deaths here in Houston were from nursing home residents which is way below the national average. And so the point is that I want to make from a practical standpoint from a local, a local guy who's just trying to do the best he can for his community, using the wastewater not only bought us the credibility and the trust that was so very, very much at risk during this pandemic. But it also became something very operational that we used, not only with the jail, and not only with the nursing homes, but as Dr. Stadler pointed out, we, you know, we also used it. You know she talked a lot about the schools but we also used it in individual neighborhoods. And so when the when COVID comes to a big population like this, it doesn't hit us all at the same time. It sort of makes its way across the city right and so there are there are neighborhoods that get hit worse than others and she mentioned this, their neighborhoods get hurt worse than others that you know at this time. And then it can it can shift around a little and then there were neighborhoods that always seem to get hit really bad and other neighborhoods didn't seem to get hit bad at all. We don't necessarily know why that was, but with wastewater we were able to have a knowledge of that. We have visibility on that. And therefore we were then able to take public health teams go into those neighborhoods which are either at risk right today, or the ones that were chronically at risk and I shouldn't say or but both, and get our teams in there we went door to door we knocked on that we talked to people and tried to educate them offered them tests, incursion to get vaccinated. And it became a very, very practical tool for us to use and I think that's the point I want to make. And I think I'm almost out of time but the point I want to make is, is in the end, it, it bought us the, and I've said this couple times now but it really it bought us that absolutely invaluable credibility that translated into trust that was so very much at risk. And then we use it to really get boots on the ground and in the neighborhoods and doing good things. As a result, I think that we can, we can probably reasonably say that in Houston we saved many many lives and certainly avoided a lot of illness and hospitalizations and days off from work, because of what we learned with the wastewater. And so, I think I had 10 minutes and I think I've talked for about 10 minutes and so thank you for the opportunity. David that was, that was fantastic I think, I think we've all recognized on the committee that Houston has been a leader in, in many ways not only in the, in the scope of what they've done but how they've, they've used and transmitted that that information. Let's open up for questions first with Cindy and any for David and then we can expand out to, to all of the committee members to make sure we have the opportunity. I did have a question for Cindy, which was, you know, apart from the pathogens that you mentioned, one of the things we're looking at is, is what kind of rare threats that are detected in other countries are now at risk for spread into the United States and obviously would perhaps be best detected at the airplane airport level, but also the risk of false positives so if we start looking for Ebola, or, you know, the MERS coronavirus back when it was spreading. You know, just positive predictive value is working against you, but yet that's one of the goals of this kind of structure so just curious in your thoughts of what, how you would approach that and what kind of verification you would want to avoid, you know, a scare that doesn't materialize and compromises confidence. Yeah, and so those are exactly the questions we've thought through or are thinking through as we do this and the goal of our program is early detection, but I don't think that necessarily every pathogen should be part of, you know, detected at the airport level, like for example, Ebola. Ebola is a clinical disease and, you know, are we, do we need to have like discrete detection because we're going to miss people. It's not, it's the opposite of SARS-CoV-2 where 40% of the people are transmitting it and they don't even know they have it. You know when someone has Ebola. So, and also the consequence management, so we're in our program TGS is really not tracking the names of the people. There's no consequence management. And so you don't really want to identify a plane with Ebola on it at JFK because then what are you going to do. So when there is an Ebola threat, the prevention really should be done and it has been done with our border intervention groups that go to Africa and work with the countries there to do exit screening, not entry screening, because we don't want to find it on this side. Obviously, nothing's perfect, but that has worked in the last several outbreaks we've had. So I think Ebola is kind of a weird one and then, you know, but we have been, we're piloting everything with our program we start small and we pilot it because we don't know we've talked to the SMEs in all the various groups at CDC when we're picking targets and we don't know. We think some things we're going to just see a lot of and other things, you know, we're not going to see, but we want to make sure that if we are seeing something that it's not a false positive. So exactly what you're saying so we're just starting small and looking at the data so this isn't with a view to like jump in and it make it it's not surveillance, right. I mean it is surveillance but it's a pilot project of seeing the capability of our program for these other pathogens. Does that make sense. It does. And Ebola is probably a bad example for the reasons you mentioned because the clinical manifestations. But you know things like, you know, MERS Coronavirus or the original SARS when it spread to Toronto and you know would you how those programs get implemented and what kind of safeguards you put for a positive detection. Just things. Right. These are all things we're thinking about. All right, I just hope you just give me the answer, but it's not quite that simple. So, yeah, or NEPA is right. I know which because it comes on people's mind and they say, you know, we've had these NEPA cases and India aren't you looking for it and we just curious about approach that. All right, let's open it up for other questions. I don't want to hog all the questions. Thank you. Thank you, Cindy. Thank you, David. Those were great presentations. I have two questions for Cindy. The first is, have you had any discussions around untargeted approaches to evaluate the triteration samples or the wastewater samples from planes. My second question is for the data that you're already collecting, especially as it relates to wastewater from planes. What type of metadata are you collecting around like flux through the airport, how full the flights are, the demographics of people on the flight. Is anything like that being collected? So, for the flights, I'll take the second question first. So the, for the airplane wastewater, we know the origin of the flight. And we know the airport for the, you know, you're at the plane, you have to know what you're collecting the sample from, but what other things would you want to like who's on the plane? No. So they're not doing demographics, like age distribution, how full the flight is. I presume nowadays most of the flights are full. Yeah. Yeah, most of the flights are full, but we're not, we're not doing that presently. Got it. And like flux through the airport, just because I understand that, you know, the flux through the airport, fullness of flights also changes from, you know, weekly and seasonal basis, you know, other things like climate, etc. But just out of curiosity. I mean, those data exists, we're not using them right now. Not to say they couldn't be used at some point, but not right now. Right. And then the other was about the metagenomic approaches. So we're really taking our lead on some of this from the news group from Amy Kirby's group on approaches that they're using. We don't want to reinvent the wheels. So we're just starting out small and then expanding. I know they have plans through like August of 24, I think is when they're going to roll out some other stuff. So we're working with them, we meet with them monthly and try and align our methods so that we're not doing something totally different. So yeah, that's all in the future. Thank you. Alright, Chuck, then Lauren, then Scott. Yeah, I'll just, you know, echo a question I see Rachel put in the chat, which is of interest to me is anybody thinking of banking these samples or potential retrospective studies, if something we're not thinking of now comes up in the future. We do bank samples, you know, obviously with banking samples, I don't know for the wastewater and I need to check with the lab, you know, we bank the RNA for the nasal swab samples, but it's just a matter of space and how long. We don't bank things for a month or two, but you know, for years, it becomes a problem. Right now we don't have that many samples so we are saving them all but as this program expands, that's a really good question. I'm getting a lot out of this I'm writing down questions that for our own program so I mean that would be something to do but I think banking is always good. If something emerges, did we miss it. And that is what happens if a new pathogen emerges somewhere that we don't know, you know, we don't have a diagnostic test for. So, how do we identify that. Lauren. Hey, so my questions for Dr first. So, we're just, if you can think about the facilities, you know that we're talking that we monitor. What do you think, or is there a use for doing facility monitoring for future threats, you know, we're doing nursing homes, schools shelters, and then jail but for public health preparedness just things that we, you know, would eventually go up is does a facility play a role in that. Oh yeah, absolutely I mean you know so the thing that comes to mind I think a lot of us are going to be flu and RSV because they made the national news and stuff but we have a, we actually have a committee that I co chair locally, and we're trying to expand out to to identify of all the things you know with grace where they're as you guys know better night but they're, there are so many things that we can test for what are the things that we should be testing for moving forward. And the, and I will tell you that the more you think about it as we engage with our local infectious disease doctors and our school officials and so on and so forth. It becomes a really complex question. And so we're struggling with that because we can't test, we will be technically I guess we could test for pretty much everything but practically we can't test for everything. So what are going to be those things which are most actionable and so we're working on that right now. And once we get that question set and we're going to, we're going to start testing, you know, prospectively certainly with the schools. And I'll tell you that our experience with the school nurses and the school administrations has been very positive. And very, very interested in, in, in learning and then, you know, and of course, once we tell the school listen you've got, whether it be flu or measles or whatever. You can imagine if you're the school nurse in the health room because hey guess what you got a measles case. You know, of course we're going to be excited but if you're the school nurse you're going to say, God, what do I do with that right. And so a lot of a lot of relationship building if we move forward and we're having these discussions now okay what if we come to you with a with a months it looks like you got months in the school or you've got whatever else is that we're testing for. Same thing with the nursing homes and with homeless shelters and again the jail which again is a completely different world. I will make the assumption that nobody on this call has ever been inside of jail other than as a visitor guarantee you don't want to be there for any other reason. But they are incredibly complex communities and when a when a pathogen contagious pathogen is in whether it be a school or a nursing home or a jail or another. You know, specific place with confined residents if you will it is incredibly complex as to how you're going to mitigate that and so a lot of pre planning has to go into it and then that's we're in the middle of now. I don't know if I've answered your question Dr Hopkins. Yeah. Yeah, I was just like thinking forward as we, you know, maybe there are things out there that we that, you know, I mean do you see an application for things that we don't that we're not looking for. Yeah, yeah. Yeah, so, right, right. So, and this is where mine now you to take comes in so let's say just to talk about code let's say we get another we don't get you know genetic drift we get a big genetic shift right. Are you guys going to be able to pick that up. Right, I do know what to look for in the wastewater or let's say, I don't know I mean, you know, when I was in med school the idea of there being an Ebola outbreak was completely off the radar right so these rare viruses are we going to be able to pick those up to you know I mean I don't know the science of it well enough but my understanding for you guys is that well probably yeah we will but but you need to be thinking about that setting it up and and even like you know recently with polio right who thought we were going to see polio and the wastewater in New York City like they found it right so we need to be able to look for what we're we needed not only look for what we are planning on looking for but we need to have the ability to look for what we don't expect to find. Alright Scott and after this feel free to open it up to any of our previous speakers as well. Cindy thank you for their presentation I think some really interesting triangulation between Rachel's presentation errands and yours. I had asked you about kind of what you're doing with the data and you said reporting to news. Yeah I think we are I'm just double checking that we upload the raw sequences to NCBI I was pretty sure that we also report to news but yeah I don't I want to double check that. So I still I'm struggling to understand how the data is being used I mean one of the concerns reporting to news that's that's fine but then there's a timing issue that I have regarding how effective the monitoring is being for for the intended use. But is there any more localized more immediate response of that data provided to the local areas the local health jurisdictions. Anything like that. So that we don't have enough data to like really get at your question we have like 120 wastewater samples so we're our crux of our program right now is the nasal sample where we have 300,000. And that those data are reported to cover data tracker weekly they're uploaded to get say it immediately after eight days. We've had a number of instances where we were six weeks ahead of the rest of the world, finding a variant, reporting it be a to be a three just now be a 2.86 that everybody had 30 plus mutations and was out of the blue in three months all at once. We found the first one in Asia from Japan from a traveler who was there from 15 to 30 days. And Japan didn't know they had it they've been doing a lot of sequencing ironically they're a high income country. They were doing sequencing but they were doing it all at the hospital and like, so, like one location so some bias sampling, and didn't pick this up just last week they and we found it in August. So, where we can, we are ahead of the game there and what we think, like the whole ideology of this is that we think wastewater from the planes will give us what we're getting already from the nasal swaps, not for everything like wastewater isn't good for for flu stereotyping right it's a segmented virus, you need the clinical sample, you can find flu but you won't know. And each one and one or what it is right if you have a wastewater sample. So there are certain things that the nasal samples are better for, you know, because we're doing the genomic sequencing and so when we find something like be a 2.86, we can tell the news you start looking for that in the community and then they know what to target and look for. So we're just not there yet like we don't have hundreds of thousands or thousands, hundreds of thousands of wastewater samples. So we can envision that at some point you know we can move from nasal sampling to the wastewater sampling like if we had enough we're doing some modeling to figure out what is the right number of airports to be at. What are the, the right number of flights to get, and then, then we can upload that data to a database and that will have the same impact on public health which is getting early detection and filling in the gaps and global surveillance. And it's not a consequence management program we can't say like, oh, Mr Smith came off flight 101 from Bangladesh and has COVID, we don't know that we're not. This is a voluntary anonymous program and the wastewater the same. Does that I just want to make sure we're all on the same page with the program. It sounds like you're basically using it to to narrow the focus on the targets and inform regarding these different strains but it doesn't look like there's an immediate public health response based on your data as envisioned. For the nasal program there is on the wastewater is new, so we just don't have enough yet we're in, we're doing it at one airport, the programs expanding and then the it should be we would have a public health response so. For example, if you find a variant in wastewater from an airplane that's a new variant. Now it'd be better if you had a site in the UK and maybe one in Singapore. And then you could talk to your global network and see if anybody else is seeing that, because what are you going to do if you find one off of something. But we'll have the sample and we can get that sample for viral characterization back to the b2.86 example. We were sending samples to the CDC lab and that happened that one from Japan happened to be. So it was even we didn't even have to wait and send it it was already on its way to CDC, and they were able to do, you know, culture in the lab here because everybody was scrambling to get one of these b2.86. So it's, it's early detection is important, because you want to know if your countermeasures are going to work. You know, it's better to find out on entry in an airport than it when somebody's in the hospital bed or when you're out of ICU beds or ventilators or whatever. It's, it's giving you that it's buying extra time to figure out your strategy. So it's really early detection and so we've shown that we can do it with the nasal sampling and we're trying to show that the the wastewater is just as good and it's low resource intensive. It's really not engaging with the traveler. It's not disrupting the airport operation. So really, it's an easier way to do because if you think about lower and middle income countries. Not every country can spend a ton of money doing huge programs and if you want to have a global network you have. This is a really good tool that others can use for early detection. But we were proving it now that's what our programs doing we're scaling up we're in the you caught us at the beginning. So I can't tell you what we've done yet with wastewater but I can tell you with the nasal samples we've been able to do some good. One last follow up and I'll turn this over are you are you suggesting then that you plan to isolate live virus from wastewater if you get a signal. I am not a lab and I don't know if that is even possible so and that it sounds like it would be challenging, I would think. So, so we have done that with nasal sampling so that that's why I was saying there are certain things that you can't do with wastewater that you can do with nasal samples. But we, we can sequence and then we can get the nasal samples we can ramp up nasal sampling like if we see something come in in wastewater from a region of the world we can increase our nasal sampling program at that airport or at several airports where we're stationed and cover those flights. So, for example, when China got rid of their zero COVID policy last Christmas, we quickly ramped up and opened two more airports and expanded hours and increased our coverage of flights in China, Hong Kong, and we were able to get like 250 flights that could have passengers from China because there were three sequences uploaded to get saved from China at the time and there were a million cases a day of COVID and nobody knew what the variant was going to be. So we use that we could scale up the nasal sampling program so if we detect something in wastewater, we could scale up a nasal sampling program to culture virus or to do what we need to do. Does that answer your question at all. I think so. Thank you. Okay. Stephanie. So I have a question for several speakers including some of the earlier ones. So if Miles and Justin can bring them into the panel. We're primarily focused on news as a national system. And so part of the question here is trying to understand the value of local facility sampling, not only for local good, which is part of what news is trying to do, but to also think about how it benefits national response. And so I'm curious from the aspect of, you know, nursing homes, correctional facilities schools, is there something that that not just how it correlates with local wastewater treatment plants but but something that needs to come up to the national level that we need to understand from this? Or is it primarily just feeding a local response? This is David first. I'll take a stab at that. Again, you know, my training is just locally here in Houston, but I will tell you that we found that when we have nursing homes, for example, we work close to them, we would get their COVID numbers down to zero and their wastewater was was clean. And then it would pop up again. And we would go in there and work with them and quite honestly what we found out it was generally an employee who had brought it in. We also noticed that what we found was sometimes some nursing home employees are full-time employees with nursing home. Others go from nursing home to nursing home to nursing home. I want you to think about physical therapists. They'll go to spend two, three hours at one nursing home, then they go to another nursing home, spend a couple hours there. Well, working with our epi, we were able to find out that in several cases it was the physical therapist who is bringing the COVID into nursing homes that were clean, if you will. And so when you talk about it at a national level, I don't know that I really have that perspective, but I will point out that we learn so much about disease control within nursing homes as an example. And similarly within schools, now with schools, it's far more difficult because the kids spend part of the day at school, then they've got all these after-school activities, and then they've got home. It was far more difficult, but working with the schools, again, we learned a lot about disease transmission within children. And so I think that there's an awful lot to be learned by doing this wastewater surveillance at Sentinel places and in specific places. Now, I'm not a national guy, so I don't want to get into somebody else's lane, but I will share with you that we learned things we never imagined we would have learned by taking the wastewater, which gave us the heads up, here's our problem. And then we started digging into it and, you know, call appealing the wires away from the onion or whatever. It's really important information at the center of the onion that you don't know to look for without the water. Mark or Rachel. Sure. I'll start. It kind of follows up on this, but I think, and I asked that question about banking wastewater samples from the airports because, you know, we do that at O'Hare. And I think a lot about the beginning of the pandemic when we didn't know when COVID came to this country and where it was and how it was spreading. And had we had a freezer full of wastewater samples from O'Hare or from anywhere really, we would be able to go back to those and see when we first saw it and when it started going up. And that's that's a kind of unique case of a respiratory virus that was spreading kind of silently throughout the country. But, you know, to follow up on those comments of transmission, like, when when we think about other infectious diseases and their transmission routes are different and their NEPA keeps coming up. Like there, there, there are different transmission routes and different different vulnerable populations. And so if we kind of to your question about, you know, how national responses to these facility level sites or sentinel sites, we can know things about like, do we see it? So C. Oris is where we're looking in long term acute care hospitals, skilled nursing facilities where C. Oris is a big problem. It's not as much of a problem. In other types. We're about to lock down at Episcopal High School. In other types. There's no anything about it. So, yeah, I think just knowing like how, how things are being transmitted and where is really useful for, for a national perspective. But, but yeah, you have to know what you kind of know what you're looking for look for patterns. And so the couple of things that that come to my mind on it are one is again kind of comes back to those levers. Are you trying to control something? Are you trying to limit something? Are you trying? Are you trying to do some kind of reaction? Are you trying to get ahead of this with the information gathering? Right. So just knowing that you have a threat ahead of you, you have the ability to start figuring out what are your plans in place to be able to try to avoid it. But I, and there are a couple of things that I kind of come to think about this when we're talking about this. So questions like this. So one is do we have a generalized plan? So is there some kind of like, so if we find it in an airport versus a train station or we find it in a hospital versus an elder care facility, there's probably a plan or there should be a plan. Please, please let there be a plan that of what we would do because we see that. The reason one that might be a piece to this that we need to think through is, what does that plan look like? How do we structure it? How does it tear up? How does ramp back down? All those things to be able to make it that we can respond that much more effectively rather than react. Because you don't want to react to something you want to respond to it in an intelligent and controlled manner. If it's more along the lines of discovery of where is this new variant going to be evolving to or what's the next threat that's going to be coming down the line that we need to be prepared for. Then that is something that probably a national network would actually be representative of. But when it comes to levers of control, that's really very much a localized area except for specific levers, right? If you're going to now control transport to a specific location or you're going to try and control movements within a specific area or specific region. And when we started up on the correctional facilities, we had a significant number of cases and deaths. We were filling up OSU hospital on a regular basis. And because we put in a number of different controls that were environmentally based and then backed it up with verifying whether or not those controls were working using wastewater. We started etching down further and further because we could start tweaking those environmental controls that little bit better. So at that smaller scale, it works great for levers of control. As soon as you start scaling that up, just like any kind of modeling, that's when your biggest issue. So it's kind of a split between the discovery side of things and getting ahead of the curve or whether or not you want to try and control something. I think one of the challenges we have in looking at this for a national wastewater system to kind of build on what Stephanie had raised is kind of the spatial and temporal distribution of testing. That is, do we need six places with a capacity and capability of Houston to inform what happens nationally? Or do you need, from an early example, from the pandemic, the front range of Utah had 42 different sites? And the question that I kind of raised this earlier with Lauren Stadler is, you know, at what point, given limited resources in the new system, you know, you can't test every site every day for local action to make a national system functional. One of our big challenges is what is the optimal, sustainable design for sampling and analysis. The clear answer is it all depends, which makes for a very short report. And one of our challenges is to try to bring some structure to that from the perspective not only of what works locally but for this national system. So welcome to have any comments on that currently or in writing subsequently. I don't know who is next Lauren or Susanna. I think Lauren was next. I was just going to make a quick comment kind of piggybacking on some of what you said, which is, you know, yeah, it really, it all depends. And I think. And also piggybacking what Dr. Purse said in that it's we've learned a lot from the facility level surveillance to understand transmission. And we've also learned a lot from pairing the facility level surveillance with the citywide surveillance and, you know, and really we should think about scale is right to the national surveillance to think about how these, you know, different scales tell us different information. And for different targets, you know, it, it might be quite different right so, like, for example, we have done some surveillance at nursing homes where we reliably detect certain pathogen targets that we don't see reliably on the streamways where a treatment plan. And I think, you know, for a lot of these new targets that are going to be diverse and structure new types of pathogens we're going to have to do this type of work again and again to really understand kind of, you know, where we can reliably detect certain types of targets, and then balance that with yeah these national goals of surveillance. And so, you know, a lot of our facility levels have is really stood out stood was stood up again for having the intervention being more actionable when we do detect that target. Yeah, thank you. Zuzana you had a comment. Yeah, and I'm not sure I will say much anything new but it's so and mark was also saying it depends on the goal right and we are now thinking about it also with the other targets and I don't think we can say sites for all targets, right that's just not going to happen. And, for example, if I want to do not a virus you know, I can do it. I can learn from it so much from surveillance I don't think we know that much I think there is so much more nor a virus and the dynamics might be possibly different than what we believe and things like that. So there is still so many things we can learn from this what about diseases but also if I want to do it as a support outbreak investigation that I want to have a flexible network where I can turn on and off base for their sampling in certain areas where I have outbreak. So, so it's just very tricky question. If it stayed by it or nationally, it was so much depends on what I'm trying to achieve and what's the target. Right, and, and I don't think there will be generalized question for, you know, for any of these we could say we could focus. If it's emerging pathogen and coming then you want to focus on airports and maybe highways, right and so again it's, it's just so depends. On the perspective person then air. Yeah, I just want to make one quick comment, you know what it comes from again this is a perspective of the local person. But what I'm going to talk about has nothing to do with wastewater but you know we had this situation with hepatitis a in San Diego that spread to Los Angeles and spread to Phoenix, and then almost simultaneously there was a slight different strain that in the pandemic. And when we got that information we turned around here locally and got with our, a lot of our local partners in the healthcare for the homeless and so on and so forth. And we went out into homeless camps and started giving away hepatitis a vaccines to anybody who would take it. Now that situation and nothing to with wastewater but the point was, you know by paying attention what was going on nationally and getting that and that was just for me reading the newspapers and so on and so forth. I got the heads up that hey something's going on up here. I've got a tool to help protect my community. And we got people out under bridges and into those homeless camps and trying to protect folks so you know that wasn't a waste water but I can't see why a national wastewater system. You know wouldn't have the same, the same ability to give us again it's an early warning system. And if it's an early warning something for something that's actionable. I now know to take action which I otherwise would not have I think, I don't know when I think when I think about this system. I think about like the traditional clinical surveillance right which is very specific but also resource intensive you need people to present for treatment. You have syndromic surveillance right which is not very specific