 All right, welcome everyone. Welcome everyone joining in person and also those of you joining virtually to our first committee member of the National Academies of Science, Engineering and Medicine, study on community wastewater-based infectious disease surveillance. My name is Guy Palmer, I'm the chair of the committee. I'm a professor at Washington State University where I serve as senior director of global health for the university. Our committee has been tasked to review community level wastewater disease surveillance and its potential value towards prevention and control of infectious diseases in the United States. If I can advance this slide. Next slide. Yep. The statement of task is presented here and that is available on the website for the committee for those of you who want to review this in depth. But an ad hoc committee and I'll introduce the committee members here in just a moment. We'll review this community level wastewater-based surveillance based on the statement of task. You can see that here, basically it's to describe what wastewater-based surveillance disease surveillance is and how it is different from other approaches to disease surveillance. We'll review how wastewater-based surveillance has been useful in COVID-19 during the pandemic and how that has informed public health decisions. We'll also examine the potential value of wastewater-based disease surveillance for understanding preventing disease and illness beyond COVID and the strengths and limitations of this approach in the United States. We'll describe the general characteristics of an approach for a national system for wastewater-based disease surveillance and discuss broad approaches to increase the public health impact, basically, how this will inform decision-making. For the purposes of this study, it's important to emphasize that community level wastewater-based surveillance does not include local surveillance at a neighborhood or institutional level. Next slide, please. And this is what will be the current focus, which is the phase one part of our study. Phase two is defined here and is present on the committee. I think for today, we're going to focus really on our phase one of our study proposal, but this is available on the committee website. Phase two, obviously, this is linked as we progress through the different phases. Next slide, please. So the study schedule for phase one, we've had, this is the first hybrid committee meeting. We'll have a second hybrid committee meeting in June with a goal of compiling this report in October with a public report release in November and then progress to phase two, which is tentative at this time. Next slide, please. Okay, the committee roster, I'm going to actually ask the committee members to introduce themselves starting with Ami. And if you just say basically what your area of expertise is and the institution you're located at. Thank you, my name is Ami Pat. I'm an associate professor of medicine and genetics at Stanford University. And my area of expertise is the human gut microbiome and measuring viruses and bacteria in human soil. Thank you. Marissa, Marissa's not here. Raul. Hello, everyone. I'm an environmental scientist at Hampton Road Sanitation District. And my background is in molecular quantification of markers in surface waters. Chuck? Chuck Haas, Drexel University, professor of environmental engineering. And my expertise is microbial risk assessment and state and transported pathogens in the water environment. Lauren. Good morning. I'm Lauren Hopkins. I'm a chief environmental science officer for the city of Houston. And I run our moist water surveillance program and public health intervention for the city. Nataki. Nataki Osborne-Jelts, assistant professor of environmental and health sciences at Spelman College in Atlanta, Georgia. My work is at the intersection of water resources management and public health. Christine. Good morning. I'm Christine Critter-Johnson. I'm an epidemiologist at the University of California Davis and my expertise in infectious disease and surveillance. Rob. Hi, I'm Rob Knight. I direct the Center for Microbiome Innovation at UC San Diego, where I'm a professor of pediatrics, bioengineering and computer science and engineering. And my expertise is in microbiome technology and data analysis. Sandra. Good morning. I'm a professor in the School of Freshwater Sciences and my expertise is in environmental microbiology and bacterial genetics. And our lab develops new indicators to track pollution sources in the environment, especially untreated sewage. Michelle. Hi, I'm Michelle Mello. I'm a professor of law and health policy at Stanford. And my work focuses on issues of public health ethics and public health law. Scott. I'm Scott Meshti. I'm a professor and associate chair in environmental occupational health sciences in the School of Public Health at the University of Washington. And I focus on fake transport, detection and control pathogens in the environment. Reika. Good morning, everybody. My name is Reika Singh. And I am serving as a wastewater surveillance program manager at Virginia Department of Health. And my expertise is environmental science engineering and public health. Nourage. Good morning, everyone. I'm a professor at the University of Southern California and my expertise is in health policy and economics. And Krista. Hello, I'm Krista Wiginton. I'm an associate professor at the University of Michigan in civil and environmental engineering. My research focuses on the mechanistic fate of viruses in the environment and their detection. And we have one other member of the committee who's not here this morning. I think she's going to be joining in the afternoon and that's Marisa Eisenberg of the University of Michigan. Before we kick off this first session, I do want to note that this is an open on the record session. This is being live streamed and will be archived for later viewing after the event, after the event. This meeting is being held to gather information to help the committee conduct its study. The committee will examine the information material obtained during this and other public meetings in order to inform its work. Comments made by individuals, including members of the committee should not be interpreted as positions of the committee or of the academies. Committee members will often ask probing questions in these information gathering sessions that may not be indicative of their personal views or the views of the committee. The committee will deliberate thoroughly before writing its draft report. Moreover, once the report is actually drafted and written by the committee, it undergoes rigorous independent review by experts who are anonymous to the committee and the committee must respond to this review with appropriate revisions to satisfy the academies report review committee. And only once the NAS president has signed off is this considered an official academies report and the recommendations held within. Therefore observers should not draw conclusions about the committee's work based on today's discussions. Doing so would be premature. Next slide. This is the agenda we're gonna start with. I think we're just a couple of minutes behind schedule. So let's go ahead and progress with that. We're gonna have an overview of the National Wastewater Surveillance System by speakers from the CDC. And our first speaker is Amy Kirby who will give us an overview of this system. And she is a microbiologist and senior service fellow at the CDC. Amy. Thank you. That's not fine. All right, thank you for that introduction. Yes, my name is Amy Kirby. I'm the program lead for the National Wastewater Surveillance System. Thank you everyone for taking the time to be here today and talk about wastewater surveillance. As Guy said, we will start with an overview this morning of the National Wastewater Surveillance System and how it is structured. In my initial introduction, I'm really going to focus on the implementation of the system and the decisions we had to make to get the system up and running quickly in the context of the COVID-19 pandemic. And then we'll dive into more of the science of the laboratory testing and the data analytics with other talks later today. So I always start with this slide. This is the four major advantages of wastewater surveillance, specifically for SARS-CoV-2, although many of these advantages will apply to other health targets as well. The first, and we recognize this very early on, is that about 50% of individuals that are infected with SARS-CoV-2 will shed detectable viral RNA in their feces. And this shedding happens whether they have symptoms or not, it happens in adults and children, and it happens very, very early in the infection. And so what that means is that by looking at wastewater as sort of a pooled community stool sample, we can get data on the full spectrum of diseases that are in a community, which is very different from our clinical surveillance, which is primarily gonna detect symptomatic and severe infections. Second, and what I think is really the most powerful benefit of wastewater surveillance is that it's independent of healthcare seeking behavior and testing access. So it doesn't matter if people go to the doctor, it doesn't matter if they get tested, it doesn't matter if that test is reported to health departments as we see now changing with the movement towards home testing. As long as that community is using toilets that are connected to a sewer system, we can get information on the overall infection levels in that community through wastewater surveillance. Third, it's a very efficient method of getting community level data. So with that single sample collected at a wastewater treatment plant, we can get information on hundreds, thousands, even millions of people in our very largest systems here in the US. And finally, it's fast. From the time the toilet is flushed until we have data in hand is about five to seven days. And throughout the course of the pandemic, we've seen that this is a leading indicator of trends in the community. So we've detect trends in wastewater on average four to six days before we see those same trends reflected in case data and about 10 days before we see those trends reflected in hospitalization data. So as I said, I really wanna focus my talk this morning on the structure and how we implemented this system. So this is an overview of the data flow for news. So if you start at the top left, of course we have communities as our source of wastewater. That wastewater flows to wastewater treatment plants where the sample is collected. The sample then goes to laboratories for testing. That data is sent to health department and then they submit the data to CDC for analysis and we report it back both to the health departments and to the public for use. But let's look through each of those stakeholders because each of them have some impacts on how the system was ultimately set up. So let's start with CDC. And I think it's worth taking a step back and thinking about what CDC's role is in national disease surveillance. And really it comes down to these four functions. First and foremost, CDC's role is to ensure data comparability across jurisdictions and over time. For wastewater surveillance, that is particularly critical because we did not and still do not have standard methods for wastewater testing for SARS-CoV-2. And so it was, this is sort of a factor, a complication of environmental microbiology, right? We don't have diagnostics the way they have for clinical testing. And so we had to evaluate these methods as they were being developed, but we wanted to put them to use as soon as there was evidence that they could be useful. And so we just chose to take the approach of letting, as my colleague Rory Walsh says, you'll hear from him later today, we chose the method of letting 1,000 methods bloom and seeing which ones are performing well over time and protecting that flexibility to be able to change methods as the pandemic evolved. And so really one of our key focuses then is to make sure that even though the data is being collected, we're using different methods, ultimately the metrics that we're looking at across jurisdictions are as comparable as they can be. Second, we of course analyze data but really we provide public health interpretation and guidance and that goes with that third bullet which is providing technical assistance to implementers. How do you design a sampling frame? What is the best way to sample and test? How do we evaluate and use this data once we have it back in our hands for our communities? And finally, CDC does a lot of summary, national level summaries of data and making that data available for states, the public as well as other stakeholder organizations. I think it's worth taking just a minute to look at what a typical surveillance system looks like and the timeline for establishing it because timeline played a big role in how news was stood up. And so I always think about news and comparison to PulseNet which is a system that was established just over 25 years ago to address foodborne outbreaks. So in 1993, there was the large jack-in-the-box E. coli 0157H7 outbreak and that was really the inciting outbreak for the development of PulseNet. So that's 1993. A year later, there was validation of the method they were gonna use which is Pulse Field Gel Electrophoresis or PFGE. And then a year after that, CDC and APHL developed the concept for PulseNet as a surveillance system. And then a year after that, PulseNet was launched in four pilot states. So we're already three years after this inciting outbreak and keep in mind we knew about E. coli 0157H7 even prior to 1993. So this is a more typical timeframe for establishment of a new surveillance system. So four states in 1996. In 1997, we have the establishment of a funding mechanism for our public health jurisdictions which is the epidemiology and laboratory capacity cooperative agreement which we still rely heavily on today. And then in 2000, they added more software to enable analysis at scale. And then by 2001, five years later, they had scaled PulseNet to all 50 states. And then worth noting that in 2015, they began shifting away from PFGE to an improved analysis method which is whole genome sequencing and that transition took three years to get all 50 states switched over. So that's a 25 year timeframe. What has news looks like? I want to first draw your attention to the fact that our arrow is now only six years represented there. So our pathogen that we're targeting SARS-CoV-2 first emerged in late 2019. In January 2020, of course, we had the first US case. And then over the course of that year, we evaluated the concept of wastewater surveillance, gathered data on how it was performing, how well it correlated with trends and cases and developed the system that I'm going to tell you about. And in September of 2020, we were able to launch news in eight states. Now, about a year later, in August of 2021, we had our first major funding round through again that epidemiology and laboratory capacity cooperative agreement. And in that round, we have 43 jurisdictions funded. So a major expansion just in the first year. As of this month, we have 841 utilities that are reporting data through their state to CDC. And that's in 44 states. For the future, so over the next three years, we're going to continue developing the system. So adding new methods, variant tracking through sequencing, we're going to be transitioning to digital PCR. So converging on a single method as opposed to the letting all methods bloom approach. We're going to be adding non-COVID targets, which you'll hear more about this afternoon from Rory Welsh. And our goal is to expand to all 50 states and also to territories and tribal nations. So very quickly, only six years from the pathogen first being identified to full 50 state implementation and sort of the full vision of what news can be. So we're under a very quick timeline and that has had some implications on how the system is set up. So that's what happened at CDC. I'm working backwards through our data flow, state and local health departments are our primary point of contact with these systems. So every state is going to implement their own Wakesport or surveillance network. And that's primarily because CDC has that ELC mechanism available to directly fund our state and local health departments to support these public health activities. And so we have been initially funding them through COVID supplements, but now we are part of the annual ELC funding cycle. So every year there's going to be an opportunity for state, local and territorial health departments to apply for funding from CDC to support wastewater surveillance. And we've been quite broad with how that funding can be used. So obviously surveillance coordination is going to be the top of the list, but they can also use that funding to support sample collection and shipping, laboratory testing, and I'll talk more about that in just a minute, IT resources to manage all of this data and make sure that it gets to CDC. Many of them have used these IT resources to build their own internal or public facing dashboards for wastewater data. And they can also use it for contract support. So if they want to contract out the laboratory testing, if they're able to support their utilities through contracts to utilities, they are able to do that. So we really want this funding to be as flexible as it can be to support the state needs. That state led implementation leads to a lot more variability when we get to the laboratory and wastewater treatment plants that are enrolled. So if we focus on the laboratories first, we see a real diversity in the way states have chosen to implement this. So some of them are able to do this testing in their public health laboratories and environmental health laboratories. And so that is a more traditional approach to disease surveillance, to have it be essentially in-house to your health departments. Others have chosen to partner with academic researchers that are able to do this type of testing. That's really where the majority of the expertise for this type of testing lay in 2020. And so they have been able to rapidly build up this capacity to do real-time testing and provide that data to health department partners. And then there are some utilities that are able to do this testing themselves. So in some cases, the utility is also the testing lab. And then finally, there's been a real boom in the amount of private laboratories that are offering this type of testing. So some of our states have partnered with private labs to get this testing done. And I'll talk more about a testing contract that CDC has put in place as well. And then that state-led variability and decision-making also has impacts on the wastewater treatment plants that are involved. We have let states make their own decisions about how they are going to enroll wastewater utilities into their system. Some of them have opted to do full coverage. So every wastewater plant in the state is enrolled. Others have targeted high-risk utilities. So thinking about large cities, transportation hubs, particularly vulnerable communities. And frankly, others have only done a few pilot implementations because remember they are building a new system while they are also dealing with a pandemic. So our health departments were very stretched and many of them were very clear that bandwidth was a limitation on how extensively they could implement news. And so we have quite a bit of variability in the scale of coverage that our states have implemented in the past year. Despite all of those barriers, we have had great growth in the news system over the past year and a half. So this graphic, Zach made it yesterday for us. So this is showing enrollment of sampling sites over the past year and a half. The dots are scaled by the population that each of those sampling sites represents. And this is both our state-led systems, which is our core news testing capacity. But we have also chosen to supplement those state systems with the nationwide commercial testing contract. So this is working with those private industries that are able to offer this testing. We have a contract that will provide testing twice a week to an additional 500 sites. This is not going to be a permanent component of news. This is a way for us to rapidly scale up coverage as our states develop their own system. Together we have 741 sites that are reporting data into news. Again, that's 44 states with data. The District of Columbia and eight tribes that have data in the system. And collectively the population covered by all of those sites is over 109 million people. So we're already at over 30% of the US population. Now, there are of course challenges. There is a hard limit to how much wastewater surveillance can grow. And that's really based on wastewater system coverage. So estimates range from 20 to 25% of US residents are not connected to sewer systems. And so they will not be accessible. Those communities and households will not be accessible by wastewater surveillance. I also like to note that while that lack of sewer coverage is primarily rural, it is not exclusively rural. You can find pockets of septic systems even within large cities. So it's always important to know what your septic system coverage is in any community that you're performing wastewater surveillance in. Also in the past 15 years or so, there has been a real movement for large facilities to do their own onsite wastewater treatment. And so not making use of these municipal systems. Importantly for wastewater surveillance, that trend is particularly pronounced with universities and correctional facilities. And so many times if you're doing wastewater surveillance in a community and there's a large university, it may not be contributing to the community sample because they're doing their own onsite treatment. So very important to work closely with utility partners to know what exactly is part of the wastewater coming into a treatment plant. We'll hear more about these other barriers going in the next few presentations, but I do wanna note that it is not easy to communicate about wastewater data. It requires careful analysis and communication and it can be a real challenge for plain language communication to the public. And one of the core messages that we really get concerned about people misinterpreting is if, for example, SARS-CoV-2 is not detected in your community wastewater, that does not mean that your community is free of cases. It just means it's below the limit of detection for this surveillance method. So we need to be really careful when we start getting into low incidence periods where we're getting negative results that that doesn't mean that we're free of COVID. We also have some barriers to sustainability of the program. There was hesitance to implement what people saw as a pilot program. I'm hearing less of that recently. So I think there, I know that with the agency, there is a dedication to this being part of our surveillance portfolio. And I think that message is getting out to the implementer community. But we also want to try and formalize some of that structure, especially around the laboratory testing and move the laboratory testing as much as we can into public health laboratories. So those are the labs that are built for sustainable surveillance testing. And we need to be able to free up, particularly our academic partners to do the research that's needed to move this forward. And we have seen wastewater data be used for many different things in our communities. What we hear most commonly from our implementers is that they value wastewater surveillance because it helps them distinguish the signal from the noise and all of the surveillance data that's coming in. And that's really because it is independent of healthcare seeking behavior and clinical testing. So almost all of our other surveillance indicators are linked to clinical care. They get skewed by many of the same drivers, but wastewater surveillance because it's independent does not. And so it gives them that check of, cases are doing something funny. What do we see with wastewater surveillance? Is it going up or is it going down or is it stable? And then they're using that information to make decisions about resource allocation. Where are we going to send additional mobile testing units? Where are we going to send additional? Which hospitals need additional support because they're going to be seeing cases on their door in the next week or two. And wastewater surveillance is really great for that near-term forecasting of what's going to happen in the next week or two because again, it's that first signal of cases in the community. And we've also increasingly seen wastewater used as a way to monitor the impact of interventions. The first use of this was a study that was a joint between NIH and CDC looking at the impact of home testing. So this was back in mid-2021. And they used wastewater surveillance as a community level indicator of the impact of this community level intervention. And I've linked you there to our MMWR which gives more details about how states are using this type of data to inform their response. So that brings us now to a really critical transition point for wastewater surveillance. We have seen that surveillance overall for SARS-CoV-2 is changing with less of a focus on massive screening tests and more of a focus on the type of indicators that would be associated with severe disease. But wastewater surveillance is still very important for providing that situational awareness. So this is a good time to really dive into what is the role for wastewater surveillance for SARS-CoV-2, but also for these other pathogens that we want to expand to. And importantly, how can we leverage this infrastructure that we have built for wastewater surveillance to get the samples collected by the utilities to get them shipped to laboratories to move all of this data from laboratories to health departments to CDC and back again and out to the public? How can we leverage that to provide the best possible data for public health action, not just now but also in the future, five, 10, 20 years from now? And so I'm really very excited to see what the committee comes up with and what your thoughts are on the potential applications of wastewater surveillance in the future. And with that, I would be happy to answer questions if we have time. I can't remember what the timing is here. Yeah, thank you, Amy. Now, we have about 10 minutes for questions from the committee. I think the... Chuck has the samples. Okay. I can't see. Oh, there's, yeah. Chuck. Hi, Amy. Two questions for you. First of all, looking at your state map looks like there's seven states that have not opted in. And so, you're insight into why that has occurred. And then my other question tackle both of ones is how about situations which they're certainly not uncommon. I don't have a sense of what the proportion is where the geographic coverage maps of the local health agencies are different than the geographic coverage maps of the utilities and thoughts on reconciling that. Okay. So the first question about the states that have not opted in, for many of them it's a bandwidth issue. So they, these were the states that were particularly concerned that this is a pilot system and that we're only doing it for COVID and then it's gonna be stood down and it's gonna be abandoned and standing up this whole new system just to have it be shut back down was more than they could accommodate in the midst of the pandemic which is absolutely fair from a resource standpoint. I am hopeful that now in this next round of funding we will be able to get some of those states on board because we have worked very hard to make it clear that this is not a pilot. This is a longstanding surveillance system. That said, I would be remiss if I didn't also say that there are political decisions in here. So some states are not interested in really engaging with the COVID response and of course wastewater surveillance is tightly linked to that. So I'm sure there's some of that in some of these states as well. As far as the geographic coverage, I guess I need a little more information on what exactly you are seeing different. Well, is it? So I mean, the utilities often serve as geographic areas that are different than the local health departments. And so what happens in a case like that? I mean, the one that quickly comes to mind based on my experience is Chicago, where Chicago has not took coterminous with the city. Yeah, yeah. I mean, that's sort of geographic boundary issue is huge for all aspects of wastewater surveillance, right? Because a wastewater systems boundaries often don't align with any other jurisdictional boundary. It doesn't align with a county, a city, a health department, any of those things. It's something that we always have in mind and primarily why most of our work is through state health departments because there you have less of those issues. There are a few wastewater systems that cross state boundaries, but they're the exception, not the rule. However, we do have some very large local health departments that run their own wastewater systems. Chicago is a great example, Houston is another one, LA is another one. And those systems tend to be, they have very close coordination with their utilities to understand where their boundaries are. We have also provided a R code that will allow them to use the geographic data within their case data and align it with their system boundaries from the utility so that they're comparing only cases that live within the geographic area of those sewersheds. So we refer to that as sewershed level case data and Zach can speak more to that. So we're trying to build as many tools as we can to address that. We can also visualize those boundaries in our internal dashboard, which Zach will show you more about. So trying to really make sure everyone recognizes that those boundaries aren't the same and we need to account for that. Yeah, thank you. We've got three questions. There'll be Michelle, then Neroj, then Reka. Thanks very much for your presentation. I'm really struck by the speed with which the system was stood up. And I wonder if you could just talk about some of the trade-offs that you had to make in order to make that happen or maybe putting it a different way. Is there anything that you would have done differently if speed had not been such a factor? Yeah, the biggest one is the method. If we had had the time, it would have been easier I think in the long run to do a full method evaluation from the beginning, identify an ideal single sampling processing testing method for news so that everybody was using the same approach. But we didn't want to slow down the implementation waiting for that. And we also didn't feel like we had enough data suggesting that a single method was outperforming the others to force everyone to one from the beginning. And then in total transparency, we now see that there are a handful of methods that are working very well but we know we're moving towards this multi-pathogen platform. So we don't want to ask states to switch to a single COVID test to then a year later come back and say, and now there's this new one that's a multi-pathogen. So the SARS-CoV-2 surveillance seems to be working well, allowing those multiple methods to be used, but we are going to convert on that single method as we expand targets. Neeraj. So Amy, thank you for your presentation. I had a couple of questions. So the first one was, what is the time lag from sample collection from a wastewater plant to actually kind of getting an actionable report? So how much time does it take to do that because I guess that would influence how actionable the data is. And the second question I had was, you mentioned that one of the limitations was that there might be low sensitivity, which is there is COVID in the community or some disease in the community and the test result would be negative. So I just want to know what the sensitivity is if there is a range that's available. Yeah, so the time lag can be very short. So it can be the shortest two to three days if there is frankly money put into making everything go as quickly as possible. So shipping with first arrival, whatever they call it, the one where they deliver by 10 o'clock in the morning and then a real emphasis on 24-hour turnaround in the lab and getting data from the health department to CDC as soon as it arrives in their laboratory. That can be very quick. However, we know there's delays at every step. What we see in our system is that from sample collection until we get data in the CDC system is about six days right now, but there is a long tail on that. And so what we are doing now is trying to identify where the barriers are to timely data transfer and submission and eliminate those and make them as small as we possibly can. For example, facilitating data submission through something like an API. As far as the sensitivity, we don't have an estimate for the national system overall as far as sensitivity. What I can tell you is our epidemiology team here as part of the COVID response has done a sensitivity analysis of sentinel surveillance systems in low incidence periods and they compared wastewater surveillance to overall case surveillance, school-based surveillance and nursing home-based surveillance. And what they found is that regardless of how they did this analysis, wastewater surveillance was always the most sensitive approach and was the first to flag in those low incidence periods. So we think the sensitivity is very, very low but we're still working to get good numbers for that. Okay, our last question is gonna come from Rekha but Scott and Christo, write your questions down because we will get to them one way or the other because they're important. Can I go now? Yeah. Okay, thank you. Thank you, Amy for a great presentation and you covered pretty much some part of my question. As you said, different states are exploring, implementing this program little differently with limited resources. So a national guidance document on not only collecting data but also on educating public would be very helpful. And I'm not sure like what are our plans to come up with that? Do we have any plans on that? Creating a national guidance document. So we do have resources that are available to our health department partners. We have not, we don't have plans right now for a overall national guidance document but I think that's a really great, a great suggestion. The challenge there is identifying who your audience is because if your audience is utilities it's very different than health departments which is very different from the public. And so we've been trying to provide resources as they're needed. So resources for the public as we roll out things like COVID data tracker so that they can understand how this data can be used to help them make decisions on an everyday basis. But yes, there is always a need for more resources and technical support. Thank you. All right, thank you, Amy. That was a great overview to get us started. Really appreciate it. Next we're gonna hear from Rachel West about building an engaging trust for the wastewater system, national wastewater surveillance system. She is a health scientist and presidential management fellow at the Waterborne Disease Prevention Branch at CDC. Can everyone hear me okay? Yes. Okay, thank you so much. Or at least I can. Okay. Great, well hopefully everyone else can hear me as well. Thank you for having me today to present to you on building community trust and engagement. I am the acting program support and coordination lead for NEWS and today I wanted to expand a bit on Amy's discussion of implementation, more on the utilities and community trust side as well as some considerations of ethics surrounding wastewater surveillance. So let's see if the slide will advance. There we go, okay. So as Amy described, this is our framework for the national wastewater surveillance system. And in my talk, I'll be focusing on what is in this green circle, our communities and the wastewater treatment plants and really how they interact with our state, tribal, local and territorial health departments. So as many of you know, wastewater surveillance really requires significant public health collaboration with environmental health. And this primarily depends on the wastewater surveillance timeliness and that depends upon our utilities sampling. So there's this cycle and building of relationships between the health department expertise, utility outreach, as well as community engagement. And we've found throughout the pandemic and throughout the history of NEWS that utilities are of course a key partner that we have not traditionally engaged quite as much in public health but coordinating with them throughout building a wastewater surveillance program really helps ensure its success and its applicability and effectively connecting these public health partners with environmental health partners early on really helps to ensure that that communication and coordination is there from an early point. So what really goes into wastewater sampling out of utility, as Amy mentioned, it requires quite a bit of input and time and so far this has been completely voluntary on utilities parts. And so this system certainly rests on their shoulders. The samples that they provide gives us more data and that provides better, more reliable trends that we can then communicate to our communities. But to get timely data, sampling protocols are best to have consistent and also if you can design that with a utility partner that is really optimal. And we would typically recommend sampling twice a week, once a week if that's not possible. And these samples can be a variety of types of samples. So it can be a grab sample, it can be a composite sample. It sort of depends on the tools that are available to that treatment plant or that sampling site. But this also brings into play staffing needs. So while everyone has experienced some probable stress through the pandemic, our wastewater utility partners of course have been continuing to serve throughout the pandemic in their own capacities. And on top of their daily duties, having to sample for wastewater for COVID-19 surveillance, it can take significant time, especially if that sampling is beyond the scope or frequency of what they normally do. And so respecting that is really important as well in understanding their capacity and their bandwidth. In addition, the shipping and storage of samples, making sure that they have adequate shipping supplies, they know exactly where the sample should be going, that can really better ensure that timely data that we need. As I mentioned, so far, utilities are primarily participating voluntarily. Some states and some jurisdictions are able to provide compensation, but this is not standard across the board. And so this is something that should also be considered when trying to implement a wastewater surveillance system and getting their buy-in is understanding truly how much this will add to their plate. And some states and jurisdictions are better poised than others to provide things like stipends or financial support for sampling. And we have heard that that aids in utility retention. So as I mentioned, promoting these partnerships early on is really key to program successes. And several of our implementing partners have actually taught us at news quite a bit about how to best engage with utilities, challenges they've faced, but we do recommend that if you are building a wastewater surveillance system, or even if you're in the midst of building it, connect with your utility partners as soon as you can. They have great insight into the infrastructure of systems. They also know their community very well and making sure to establish that relationship early on, not only for coordination purposes, but also for trust purposes and for sharing data, that can really benefit that relationship and strengthen that for the future to ensure that you retain those utilities and you're able to sample regularly and in a timely way. And so this would include early consulting of the utility capacity, really better trying to understand what they can really handle. Is that twice weekly sampling? Is that once weekly? Is it once per month? How long will it take them to find a shipping location to ship these samples for more remote utilities? That can be a significant amount of time. And so utility input and designing that sampling plan can really be helpful, not only for the health department to understand what kinds of samples are available, but to better establish what the sampling time is, what the frequency is, so that everyone is on the same page about expectations. And then regularly communicating that data to the utilities. Some of our implementing partners have been really wonderful about doing this, but although public health action primarily resides with the health department partners, utilities are providing these samples and they really value seeing the data. Not all utilities may be interested, but it's important to recognize those that would like to see the data and better understand what's going on in their community and how they're contributing to that. They're also very interested in how the data are being used, which I'll get into a bit more when we talk about ethics of wastewater surveillance, having that clear purpose of data use. And then continuing to have consistent meetings really helps with utility retention. So better understanding challenges as they arise, if there's a temporary challenge that may disrupt sampling or if there's something major coming up, if there's a staffing shortage or if someone is moving on from their position, better coordinating that so that all of the correct points of contact know who the other one is, that is also really important in maintaining high quality data. So at News we're really working to better support utilities and this is through some of our partnerships with other federal agencies as well as partners like the Water Environment Federation who have a great rapport with utilities and really understand their needs. One thing that we are also focusing on that Water Environment Federation has some valuable connections with with more rural or remote utilities that have different challenges than our urban utilities that are understanding what those might be and how we can support them. We're also trying to explore methods and ways to financially support utilities. Right now our ELC funding, our states and our jurisdictions are able to use that funding in some cases to support utilities. But we still wanna find other ways to do this so that we're showing utilities how important they are to this effort and trying to support them as best as we can. And further, we're now working to provide more tools to aid that health department in utility communication. So in our internal platform decipher, we have utility reports that can be downloaded and provided directly to the utility that provide a subset of data and metrics. It's kind of a quick look at what is going on in your community but we've provided that so that it's a very easy way for data sharing and that might promote further conversations. Now, of course, we have to move beyond the utilities and also discuss community trust. And Amy discussed our implementation at state and jurisdiction levels very well already but one of the things that we have found and we've heard from our partners is that community trust in the data really is bolstered by regular data sharing and also through communicating public health action. So how are these data being used? Are they being used to improve mitigation measures? Are they being used to help with resource allocation and help hospitals understand when surges might be coming? And on this slide, I have one of our implementing partners dashboards that's public facing. This is separate from our COVID data tracker but they use data from our internal dashboard decipher and they're able to create their own dashboards and this can be tailored to community needs. This is one of several I'm happy to say dashboards that our implementing partners have created but these types of tools to really bring the community in and involve them in the data have been really valuable in promoting that trust and in educating the community on what wastewater data are, what they can do and what their limitations are. And one particularly valuable element of that is understanding how to integrate wastewater data with other surveillance data and really using it to better understand community health. So sharing that purpose and the why behind the data collection helps strengthen community buy-in and it also provides transparency in that we're collecting this data but it's for this purpose and then it can help show the value of the data so that taxpayers know where their dollars are going and what they're supporting and how it's really helping keep their community safe. So to sum all of this up, of course, we have our state health department expertise and support. They have a great view of multiple communities within their state and what priority areas may be. And we also try to have discussions with our health department partners to better understand what communities might most benefit from wastewater surveillance, which might be historically under-resourced, which may be vulnerable populations, especially rural communities, we're trying to reach them more. And as Amy mentioned, some communities may not be on a sewer system and so this might not be the right solution for them but for those that are interested, we really leverage expertise with our state health department partners to better understand how we can implement systems and how we can support them in expanding wastewater surveillance. Oh, I'm sorry, the graphic got a little bit squished. Also, leveraging local health department expertise. Our state health departments have amazing expertise in so many levels, but our local health departments, we get really great feedback from them and in some cases in very large jurisdictions, the local health departments help us understand what's happening at a more granular level and they can really help design wastewater systems, no limitations of the community, whether that's the wastewater systems themselves or better helping us understand, oh, is this a community that experiences a lot of tourism or is this one that is really more residential? And then of course, utility infrastructure and knowledge, as I mentioned, that's really important in designing these systems. And then of course, understanding public priorities for wastewater surveillance and for public health, what are they concerned about throughout the pandemic? Of course, there's been SARS-CoV-2, but as we move forward with looking at other targets, what are their priorities and what are they concerned about and how do we communicate and educate them on what new targets we might be looking at and why we're looking at them? So part of really this public engagement is building trust and one way that we're really interested in exploring further in the future is ethical considerations around wastewater surveillance. So this is a relatively new public health tool in the US and wastewater samples are very rich. There are many microbes and there's a lot of genetic material. And currently, of course, there's no way to have individually identifiable genomic information in these samples, but it's important to acknowledge how rich these samples are, especially when thinking about a future use of samples. We also want to acknowledge that we're bridging environmental health and public health with wastewater surveillance. And while clinical public health surveillance has precedence and guidance for ethical considerations, environmental health, especially with wastewater surveillance is still growing in that area. And so we really want to try to bridge those two, those two important branches of wastewater surveillance so that we can better tailor ethical considerations and communicate these to the public. Why are we using these data? What will they be used for in the future? What are limitations? And we've encountered some of this with jurisdictions concerns about surveillance data and how they communicate that to the community. And we think it's important to acknowledge that and really listen to their priorities and concerns along the way so that we can better establish trust. So building trust in the system, a very complex goal, but one way that we're hoping to do that is through ethical considerations. And so right now, ethical guidance surrounding wastewater surveillance is largely at the local level or through academia. And when I say local, in some cases those are states or entire jurisdictions, but we don't have sort of a centralized guidance or considerations around wastewater surveillance and wastewater surveillance ethics. And all this is valuable and these efforts are really interesting and provide valuable insight into what we should consider. At news, we feel that it's important to sort of bring this to the national wastewater surveillance system stage and better consider these. And this is something we're really interested in the committee's feedback on is how we can properly do that without too much bias from our side, but also engaging the right people in considering these ethical priorities. And so especially for future use of wastewater data and samples, considering different relevant targets to public health, what pathogens are we looking at? Are we looking at chemical targets? Why are we looking at these targets? Is this because it's a pathogen that's very prevalent or is this really more specific to a certain community? And what will these data be used for? Is it for hospital resource allocation? And again, how will these data be communicated? So all of these factors, just for different pathogen targets, could be really important for ethical considerations. Archiving samples particularly, future use is always unpredictable, but we have learned in public health history that future use can be fraught with ethical mistakes and violations. And that can really erode trust with communities, especially his communities that have been historically underserved or oppressed. And one of the valuable parts of wastewater surveillance is that we can use it to reach these communities and hope to find health disparities so that we can address them properly. But first we have to build trust in those communities and maintain that trust. So understanding future use and what limitations might be around that. We can't predict what technologies might come in the future, but in at least keeping this in mind, we can try to guide ethical principles around this. And then of course social and political consequences of surveillance data. This is not quite as relevant for SARS-CoV-2, but for future targets, whether that's pathogens or otherwise, we need to better understand and ensure that there's no stigmatization of communities. So far we've actually gotten positive feedback that this wastewater surveillance for SARS-CoV-2 has not led to that, but for certain targets, we do want to be mindful of that, that we're doing this for the good of the public health and the community and that it's not misused in any way. So I mentioned that there are several efforts and ethical guidance on wastewater surveillance. One of them is not particularly on wastewater surveillance. It is general public health surveillance ethics guidance published by the WHO in 2017. And this has 17 different guidelines that are broadly applicable to public health surveillance. In some cases, not quite as applicable to wastewater surveillance. And that is where Canadian Water Network really did a lot of work in 2020 and 2021 to analyze those guidelines and tailor them to wastewater surveillance. A lot of their considerations focus on the use of the data, as well as data quality and how to communicate those data. Currently, there have been some more recent academic group publications about ethical considerations in wastewater surveillance, which is really encouraging to see and always happy to see them sort of leading that and thinking ahead. But again, that's not particularly centralized. And with state and local public health initiatives, those are also incredibly valuable. And on the news team, we want to learn from those. Every community will be different, but what are some central themes that we can find? And then on the legal side of ethics, the legality and sort of ownership of wastewater. So when you think about consent, when it's human waste, who exactly consents to that sampling? And currently it's the utilities, because it is human waste and the sampling point is at the utility. And the EPA's Clean Water Act has some sections that are applicable. And they gave a great presentation at the Water Environment Federation conference a few weeks ago. So, oh, I'm sorry again about this graphic, but there are some major ethical considerations that I've already mentioned, but just sort of major themes that we've seen so far is understanding the shared benefits of surveillance, including how these data are used, but also posing those relative to potential risks. And a lot of these center on privacy, very little in life has zero risk, but this is part of the WHO guidelines on public health surveillance as well, is really communicating the shared benefits of these surveillance programs. The opportunity and responsibility to address health equity issues and not only address them, but learn from the communities that are impacted by health disparities and better tailor systems to serve their needs. Also respect for individuals and balancing that with a need for privacy. One beautiful thing about wastewater surveillance is that it is essentially a large community pooled sample. And so there aren't too many privacy concerns. We don't sample at a household level or even the neighborhood level, but just considering that and really communicating that to the public, that can be really important. Sometimes it's just getting the answer to your question that you need. And so thinking about that in wastewater surveillance ethics will also be really important, especially when you start thinking about facility level sampling. And then of course the responsibility of those performing surveillance, the transparency and proper governance behind those structures, and then justice when it comes to misuse or violations of trust. How will that be handled? And so finally I'd like to end on a positive note that we have an opportunity to build an ethical integrity from the beginning. We have been building at these systems for a little over a year and in some cases even more, but we have learned from history that public health has incredible benefit on or that and acknowledge it. And while future use might be unpredictable, we can't exactly know where technologies are going. If we have regular review and input from served communities, from experts in public health and environmental health, then we can hope to have these ethics evolve alongside the technologies so that we can have a really strong trustworthy system that the public depends on for their data. And with that, I'm happy to answer questions and thank you for your time. Thank you, Rachel. We've got about five minutes for questions. Scott, I see your hand up and go ahead. Sure. So Rachel, there's very nice presentation for it. I'm struck by the fact in Amy's talk, she talked about decentralized systems not really being included in this. Yet it strikes me as basically in the kind of the world south and southeast in particular, a lot of these inequities or really may lie in that division between decentralized and centralized systems. And so what consideration has that been given in your thinking? A good point. I think this is where, of course, we're going to have to learn from our partners in any ethical guidance that we create or that others create in partnership with us because there are so many different systems and as some folks may discuss later on, every community and every utility is different and complex. And so understanding those decentralized systems and their needs and what ethical considerations we may have to give to them and tailoring that, it may just be that our ethical considerations are very extensive and have different applicabilities. But that's something that we should certainly think about in the future. And one thing that I'm particularly interested in on feedback from the committee and from others is some of our local and state jurisdictions who have been engaging with ethical discussions with their community. They have community representatives, a little bit similar to IRBs where there's a member of the community who may be a trusted member who can then present community priorities, questions and needs. Very difficult to do that on a federal level, but I would really be interested to hear how that might, we may incorporate something similar to not only represent utilities and public health interests, but also really community questions and understand what their concerns are. So, but thank you for that question. That's something that we should certainly keep in mind in the future. All right, we've got three questions. Michelle, Rekha, and then Rob. So it would be a little bit delayed going into our next talk, but that's okay. We want to get those questions in there. So, Michelle. Thanks so much for the information that you provided. I just pick you up on the last question. I would like to hear more about whether you are currently hearing concerns from community groups from members of the public, or is this at more at the stage of kind of issues, spotting potential concerns, but not yet needing to be responsive to stakeholder groups that have emerged in the public. So happily it is a ladder. We're thinking we're trying to think more proactively about this. We actually have heard some great feedback from our implementing partners that the public really do value these data and Zach will talk more about our public facing data on COVID data tracker. But we think we've heard that one of the valuable aspects is that it's community level health. So really looking at your entire community and how COVID-19 transmission is going. There were some concerns early on at facility level sampling, and this was primarily with universities. Some jurisdictions had concerns about privacy. And so that's why I mentioned it, facility specific levels, particularly when you think about if it's maybe a correctional facility or something like a dorm, really understanding how that data will be used is very important. So while we haven't received much feedback on ethical concerns from the public at this point, we want to be forward thinking and start trying to incorporate them now so that in the future as we expand wastewater surveillance that we at least have that in mind. And there might be some concerns that come up in the future that we haven't even thought of yet. But yeah, so that's kind of where we are. Sort of proactive thinking. Rekha. So thank you, Rachel. It was great to hear your talk in detail. I was always working with you to enroll more sites from Virginia and thank you for your support there too. We have lots of sites in our commercial contract and under our community surveillance. And thankfully we got really good positive feedback from our public. We didn't, we never heard any concerns so far, but a lot of interest in this data. My question is that, like I just said, this data is very rich and we need to work on ethical framework and guidance. So, and you just mentioned we are taking a proactive approach than reactive. Can you just explain that a little bit more like where we are and how long will it take to set up a solid framework there? So on the CDC side, we're working on the news team to sort of better understand core ethical principles that we want to prioritize moving forward. But thinking about ethics as a whole, especially release of water surveillance. We are really interested in hearing from the committee and from others, potential solutions for an ethical evaluation or ethic considerations that is not run by us because we are running the national wastewater surveillance system and it would be inherently biased if we created the ethics for wastewater surveillance. And of course we are not the only stakeholder. There are so many other leaders are implementing jurisdictions. We're so glad to have Virginia's participation, but we want to have it as a balanced approach. So we would value having a seat at the table, but we're interested in finding the best possible way of having these ethical principles shaped by as many stakeholders as we can. And we can't of course include literally everyone, but we would value the opportunity and any ideas that people have on how we could best do that, how it may have been done with other systems so that we're not providing biased guidance. Rob. Thanks Rachel for a great presentation there. I was intrigued by your comments on future use, which obviously is very important ethical consideration. Are there any specific future uses that you're concerned about with these samples? So for example, reprocessing them for drugs, reprocessing them to identify individual human subjects. You might be in a particular catchment region or that kind of thing. Or is it more of a precautionary principle where you think there might be some future use that people would complain about, but you haven't figured out what that future use would be yet or is it a mixture of both of those? It's a little bit of both. As you mentioned, so if wastewater samples are archived, one of our considerations and concerns is who will have access to those samples? Who will be able to request access and how will they be used? As you mentioned, things like illicit drugs. In some ways, we're seeing epidemics of drug use throughout the country. And so it is a public health issue, but there are also stakeholders in that on law enforcement side. And we want to be mindful of that in that could these samples be used for something other than public health? And so illicit drugs is something that comes to mind. In certain cases, depending on the granularity, there could be pathogens that may be stigmatizing. That is more of a theoretical concern, because our primary pathogens that we're hoping to target in the future are things like foodborne pathogens and have a very clear public health use. But I think the central concern right now is sort of where that line blurs between public health use and other use, whether that's for law enforcement, whether that's private use of samples for some type of campaign. That is a much more theoretical concern. And of course, in the future, I'm not exactly sure what technologies would be available. So what could you glean from these wastewater samples? How could this be used in other ways? But one of the primary concerns right now is essentially what target would be used and essentially who would have access to the samples to look for those targets. I just want to ensure that any samples would be used for the good of public health and not for any other unintended use that could concern a community. Grace, thank you. And our last question, Lauren. Thank you. So my question is about samples that are not collected by news. We are, I mean, in my experience, we have researchers that would like to have samples. And I'm thinking about the, the, and, and, you know, the idea of having something like an IRB or some kind of committee that looks at the use of samples. And the way we deal with it now is we have, like at least in Houston, we have perhaps an MOU with another with the utility and the researcher that's looking into the sample. But I'm struck by, I think your presentation indicating that we really don't want to put more regulation on the utility. It's a lot of burden on them. People requesting additional samples and how the flow would go. Are we going to try to restrict who gets, you know, the samples that are going forward, not necessarily in the framework of the news system. I didn't know if you thought about that. So that is a wonderful point. I'm really glad you brought that up about avoiding more intensive or additional regulations on utilities. Sometimes when, sometimes when interacting with utilities, of course, when sampling starts, there's concern. Is this leading to another regulation? Is this something else that we need to start preparing for? And our goal at news right now is not to increase regulations on utilities. We value the samples that they provide us and we want to support them, but you are right that we don't want to start over burdening them, whether with requests for samples or with any regulations surrounding that. So I think when I mentioned bringing environmental health partners to the table, that would be important to bring utility partners as part of that, of course. And better understand sort of what would be the limitations. There may be a finite amount of sample and that may just be the case, especially initially. But that is something that would probably have to evolve as the system grows and is interest in wastewater surveillance grows right now. It's primarily focused on SARS-CoV-2, but if it does blossom into foodborne illness surveillance and there's significant interest in that, we would probably need to review the ethics surrounding that and also the capacity of utilities and keep that in mind. So that's a really interesting point. Thank you for bringing that up. That's something we should certainly think about. All right. Thank you very much, Rachel. That was very much appreciated. And the question is very helpful as well. Next, we're going to hear from Zach Marsh. Zach is an epidemiologist at CDC and is going to speak around data analysis and use. Great, thanks all. Let me just get my video started. Okay. So I'm going to keep my video on, but if we start to hear any degradation in audio, just let me know. I'll cut it off. So like I was introduced, my name is Zach Marsh. I'm the data and epidemiology lead at the national wastewater surveillance system. And I just want to give a really quick overview of our data analysis and use. So you've heard a bit more about the implementation of wastewater surveillance, but what happens whenever data gets to us and what do we do with it? Let's see if I can get it. Yeah. So a slide you certainly haven't seen today already, but really what I'm going to focus on here is in the upper right quadrant. So from the data submission components all the way over through data analysis and information sharing. And so what are we doing with these data? So as Amy mentioned, one of the first considerations and really key values that news brings to wastewater surveillance is this national standardization of data. So making sure what's being captured and compiled by CDC is comparable. The methods may be different, but the data that we are collecting is similar. It does go through the same data quality standards. It does get the same exact data quality review. And it really helps to make comparison of these national level data much easier. So what I've highlighted here with the graphic is just the different components that we capture with news data. So we get information on the wastewater treatment plant, where it's located, what its capacities are, what additional inputs there may be into that system. We get information about what is, what are the factors at sample collection. So what the day is, what pH conductivity other factors, what the flow was at that system during that time, the type of sample that was captured. And then we get information after the sample has been submitted to the laboratory on what exactly they did to process that sample to get the SARS-CoV-2 concentrations at the end, which is really the final piece of information. So we get test results and all the associated metadata with that PCR result. So after all these data components are compiled into our submission template, we receive it in our data platform at CDC. Once it's uploaded, it goes through some automated quality control checks that are applied to all data in our system. And so if they don't meet the data standard, they're not going to pass along to our analysis, which is also an automated component. So once we have these error-free data, so we've gone through the quality control check, we have an analysis pipeline that's built within the same platform that data are submitted and visualized. As soon as these data are received, they initiate in the pipeline. This is about as near real-time as any surveillance platform I've worked on. It takes probably from submission to visualization 15 minutes to an hour to be able to see the most recent samples that a utility or not a utility, a jurisdiction is uploading to us. So the first step whenever we start to analyze these data are to take the concentrations and to normalize them. So we have two different approaches there. We do flow and population normalization, and that really helps to account for the number of people contributing waste and also the flow rate. As many of you may know, there can be different contributions beyond just household waste. There can be industrial contributions. There can also be stormwater combined systems with sewage. And so understanding the flow is really important to know what dilution factors may be present within the wastewater system. We also can look at factors that we call human endogenous control. So examples being pepper mild model virus. And that allows us to have a bit of a control that is inherent in the feces that are excreted within the system. And so this helps us to get a bit more to a per person contribution of the SARS-CoV-2. So after we've done this normalization, we then go through and process some metrics that we have within our system. These metrics are calculated on the per site and target level. So we can receive PCR results for total SARS-CoV-2, which is what we often are talking about when we're discussing wastewater. But we can also look at specific mutations within the genome that are very specific to variants of concern. So Delta and Omicron. So the three primary metrics that we have, and you'll get to see some visualizations of those on subsequent slides. First and foremost, we have a percent change. So our wastewater level is going up or down within a given sampling location. This is performed by a time-based linear regression. So we take all the samples within the given time period. And we run a regression on them over the number of days to see what the trajectory of those concentrations are at that location. And then just to back calculate that from the linear regression, we multiply the slope by the number of days included within the time period just to oversimplify that. The next metric we have is a relative level. This is the most recent metric we've released publicly. It takes all the wastewater concentrations for a given sampling site since they started collecting. It orders them, and it gives a sense of how high or low are levels at a sampling location compared to how they've been historically. Looking at when sampling started is a really important consideration that I'll talk about in some of the challenges later on. But this is really helpful to understand where a given location is compared to where it's been throughout the pandemic. And then the final metric that we have is a detection proportion, so really simple. It's the number of samples that were tested. And then you divide how many of those samples had detectable virus. So among all the samples that have been conducted in the last 15 days, what proportion of those found SARS-CoV-2. And so this is not so helpful when you're in a higher incident state, but as we're getting to lower incident states as we are now, it really helps to drive home where and where you are not detecting coronavirus within communities. So this is one of the dashboards that we have available. This is our internal decipher dashboard, decipher being the data platform we operate news within. So I'm going to walk through a few of the key visuals that we have available to health departments to help drive those public health decisions that they have that they have to make based on these wastewater data. So in the top left, when you load up the visualization dashboard, we have your map with a national level map and each sampling site is represented by a point. And the point currently as shown in this figure is colored based on the percent change. And so our wastewater levels going up, which are the reds, the orange and yellows, or are they going down to represented by the blue colors. And so this gives a national perspective of what's going on in the community. You can zoom in to see smaller geographies. You can select points. And you can also change the metrics. So we can view all three of those metrics I highlighted on the previous page on this national level map. If you then zoom in, I'm going to use North Carolina as an example here. You can apply some spatial layers that we really think help to provide that context to what's going on in the community. So we've ingested some spatial data on things like vaccination, testing, cases, hospitalization, and we are displaying that at the county level. What you're seeing here is the proportion of the total population that has at least one vaccine dose. And so you can have these data underlaid with the wastewater testing data on top. So that may provide that additional context to understand why some communities are seeing increases whereas others are seeing decreases, or if there's anything at the county level that may explain why you're seeing clustering of cases or clustering of increasing wastewater levels that you might not be seeing in other areas of your jurisdiction. So if you click on an individual point, there's an entire charts pane that appears in the dashboard. And so that's showing a couple of the visuals in three and four. So the visual three is probably one of our most popular. There's a few different data components that are displayed here. So for this individual site, if you've selected one of these points on the map, you get to see the wastewater concentration data that's shown by the dark gray point. And the dark gray line, which is just a smooth line of the concentration in the back, the lighter gray color and bars. That is the sewer shed level case data. So that's something that Amy had mentioned in one of her answers. So some of our jurisdictions have taken their sewer shed level spatial data. So the shapefiles that represent those service boundaries and they geocode cases to those geographies. And what you get is you can see over time what the cases in that specific catchment area that we're sampling wastewater look like for cases. And so as you can see here, we're seeing that really nice leading indication with the Omer Compique in December and January at this site. Just before you start to see the respective increase of those cases in this sampling location. So, and then in number four here at the very bottom, this is displaying a heat map that we show within decipher for a given jurisdiction. So these are all of the North Carolina sampling sites. And what this is showing is a time series. So each line on this chart represents all of the samples over time for that location with the location you've selected denoted with this rhombus or diamond shape. And so this is a really helpful visual to see how wastewater levels presently, which is represented on the far right compared to what's being sampled over time since sampling started. And so this both gives you how things look presently within a site. But you can also compare sites that started sampling around the same time periods to each other to see if levels in some locations are higher than in others. So in addition to this deciphering dashboard that I just walked you through, we have three different data products that are used by different audiences and they were designed as slightly differently for that very reason. So the decipher dashboard provides much more granular data. You can really dive in to super specific location information. You can see the sewer shed shape files that represent where these locations are geographically. You can see full time histories. You can download data from our dashboard if you want to do additional analysis of jurisdictions to use it on their own internal dashboard. We also have a COVID data tracker. So this is our public facing wastewater dashboard. It's just went through its second revision. So we now show percent change, detection proportion and the most recent additions we had. We're showing the current level. So how high or low or wastewater level compared to how high they've been since December 1. That's shown in the top right screenshot there. That's a screenshot of our COVID data tracker site. And then we also have a couple of different weekly reports that we put together for agency and White House level leadership. So there's a weekly report that we run that's been generated and are and that's really used to keep national level awareness of what's going on. And then we have a bi-weekly slide we put together for the White House that highlights some areas that we're keeping a close watch on based on their current wastewater trends. So these different products have different audiences. And as a result, the intended use for each of these are different. So the internal dashboard really for health departments to see what's going on in their data and use it to drive that public health action, which is why we provide many different data sources together in the same location. COVID data tracker is really for public to use this to inform their own decisions to see what's going on in their communities or the neighboring communities to make the decisions that are best for themselves and for their families. And then these weekly reports really are meant to just provide high level awareness to agency leadership and White House COVID leadership to make sure they know what wastewater data are showing, where areas might be emerging as far as disease goes, and then use that to inform decisions and other recommendations that they might be putting out. These data as great as they can be with all the benefits Amy has highlighted, such as the healthcare agnostic nature being very quick to get actionable data. They're not without challenges and issues that we have been working through trying to solve. The big one is the data comparability. So in addition to just variability with testing methods, there's also variability in wastewater infrastructure. So the systems themselves have different times of residence. So the time it takes to go from a household to a treatment plant may differ. There's different inputs like I highlighted, such as stormwater or industrial waste that may have chemicals that degrade the viral RNA. And then wastewater is a community sample. It's a pooled sample. And it's based on the input from that community. That includes people who may be traveling to a community that don't live there. So tourism does impact wastewater surveillance. And so it's important to keep that in mind. As I showed on the relative level heat map, you can see that within a given jurisdiction, when a sample was started or when a site started collecting wastewater, it impacts what the current picture is. So if you look at these top sites, they started sampling much later than some of the lower locations. And so they didn't necessarily sample during these peak periods of Omicron. So what they're seeing right now as relatively high might be different from those who sampled during the peak of Delta or Omicron within the pandemic. And so they don't have that pandemic memory is what we've coined that other sites may have that have been sampling for longer. And that impacts interpretation. And then it's important to keep in mind when looking at the data coverage. And then the last challenge is really just data coverage. We've highlighted and talked about the variability and geographic coverage. But there's also sampling frequencies that can be challenging to some sites do as high as five or seven samples per week. And others do one sample that we get per week. And when you do these analyses, sometimes that's not apparent. And so it's important to keep in mind that these coverage and also the temporal coverage may vary. Amy highlighted the septic challenge that we have where these people may not be able to be covered. There are also challenges with aggregating to higher geographies that many in public health often like to do of giving county level summaries, state level summaries, national level summaries of what's going on. And because of the variability in spatial and temporal coverage, that can sometimes be a challenge. That's why we often look at wastewater data on a site basis because this is a hyper local metric. And it's really important to keep that in mind. There are ways that we're exploring to aggregate, but it does present challenges on how to make sure it's representative of the number of sampling locations within a given geography. And I think that one more thing. So obviously there's been a lot as Amy's highlighted that we've done as a system, but there's still much to be done. And much we can do. And so some of the future things we have ongoing or we plan to incorporate in the future. We're looking at ways to evaluate different percent change calculations to account for sampling, frequency, factors that are intrinsic to the wastewater systems to make these percent change calculations a bit more comparable, maybe less sensitive and lower incident settings. We also are looking at ways to use lessons learned from other systems that have developed these alert algorithms to identify meaningful increases. So we're working closely with our syndromic surveillance colleagues who have some really great algorithms they've developed to identify what meaningful increases may be occurring in wastewater and to be able to parse out that noise that sometimes it's inherent in an environmental signal at a community level like wastewater. To address some of the tourism challenges or population movement challenges, CDC is acquiring some mobility data sets. And so we might be able to use that in the future to observe what's going on in these communities to see if mobility and increased tourism might be accounting for increasing levels or to discount that is happening and maybe help us to confirm that what we're seeing is based on the residents of those communities. And then the last thing that we're actively working on right now is the ingestion and analysis and visualization of the wastewater sequence data that many jurisdictions in our commercial contractor are collecting and then pairing that on the same internal wastewater dashboard that we have with the PCR testing data. So it provides that complete picture of variance in addition to just levels and trajectories so that people understand what might be driving the different levels and concentrations that they're seeing. So I think that's all I have and happy to take any questions given the time. Thank you, Zach. Very helpful and and certainly our committee members have learned how to game the system by raising their hands before the presentation is over, which is the evidence that we have a very intelligent committee. Scott. I jump in a chomping at the bit here on this one. I've got several questions for you. I'll try to streamline them into two lines of thinking here. One is the normalization of data and I'm curious if you can provide us some information around this. Why you're using a biological indicator. Like mild model pepper virus, which has natural variability of a couple orders of magnitude in addition and how you're factoring that variability into your normalization. That's my first question. The second question comes down to the matrix effect really in the individual samples and you said there's a significant amount of variability within the individual infrastructures, but the actual can be a significant amount of variability between samples as well with precipitation and just overall wastewater strength. And that can lead to single samples that have significant signal increases, particularly if you're normalizing with with indicators. How is that have an effect on your, your, you know, initially people talked about trends analysis, but single samples that are three orders of magnitude higher may drive that trend for a very long time, even though it is a spurious result potentially. And then I also have this question that the metrics piece. A lot of the utilities have changed methods since they began as methods have evolved. And so how is that accounted for in that overall historical metric that you're using? So those three questions, the historical metric, the normalization data and the matrix effect on single samples. Yeah, those are, those are really great questions and they're certainly the things that we've been trying to tackle. To I'll answer them in order in which they were asked if I, if I can recall them. So getting back to the human endogenous factors. We actually don't restrict it just to one. We allow a variety of different factors to be reported. So anywhere from chemicals to microbial indicators. And so we haven't really done an in depth analysis as to the the variability within those. That's certainly something that we're, we're wanting to explore in the future. It, it certainly does have an impact. I think some are looking at things like caffeine or, or other factors that maybe have a more stable lifespan or stable coverage and are not dependent on diet as heavily on those. Certainly caffeine does have a diet dependency, but it's something we'd like to look into more. Regarding the variability of the matrix. Yeah, the trends factors actually something we're looking at now with some of our statisticians to see if they're, if we incorporate these additional infrastructure level factors and in different contributions to the wastewater network does that help to smooth out and, and eliminate or at least dampen some of the noise that are inherent. If you look at the point level data on that figure I showed, you do see spikes here and there that sometimes we're not clear if it's a factor of the system, if it's an actual signal or if it has to do with population changes. And so something else I'm really curious about is if we can use mobility data to get a better grasp on what the true quote unquote population served for the system is rather than just relying on what utilities report to be their population serve because having that dynamic value might help us to better account for large changes in swings in population. And then the last one regarding the methods. We do actually account for changes in major lab methods. So a jurisdiction will report if they've changed an assay or they're using a different supplier or whatever it may be that they feel has deemed their results in comparable now. And so we use this field called major lab methods within our analysis and we don't analyze samples that were captured using different methods. And I didn't show an example of a site that has changed, but we do have some states that are starting to consolidate their testing within their own state lab. And so we're not going to be showing compared metrics or other trends for those sites that have since changed the method. We only compare data since the new method has begun. And you'll notice on our COVID data tracker site, if you click on sites that have since changed, the concentration time series won't be available for those locations just so you avoid that direct comparison of locations. All right. Thank you. Just so those of you joining, we're going to go till about 15 after because we do want to get all these questions in as well. Christine. Thank you, Zach. That was that was really, really exciting. And I think the dashboard work that you've done is incredibly impressive, especially over such a short period of time. I think we're going to be really interested in the data that you were showing around the lead time between the detection and wastewater in cases reported in the community within sort of that sewer shed as you're describing it. And I'm wondering if you have any data on sort of the, the number of days, if there's variation in the number of days by state or utility and just sort of what that, what that metric is looking like. Thank you. Yeah, that's a, that's a good question. We at the very early stages of the system, probably back in 2020. So before we had all the variability and we, we had new variants and everything, we had looked at the timing of wastewater in cases. And it was found that around four to six days is the typical lead time you would see with wastewater relative to the case data. We think there's been some change, obviously with different surveillance biases that are inherent in the systems. Different states have different case reporting capacities. Their clinical testing may be very robust. And so they may get results very soon. And obviously that's going to shorten the time that wastewater has on clinical testing. If they've established near real time data transfers, if they have really quick, rapid antigen testing or other mechanisms to get these data, that that's going to make wastewater less of a leading indicator. But I think on, on the average, especially now that we're seeing less clinical testing, wastewater is certainly being viewed much more I guess closely because the, the data that are available out there for clinical testing are becoming less and less reliable. The reporting frequency over just the past few weeks we've heard has decreased in most places to weekly. And so that certainly means we need to reevaluate how wastewater leads other indicators. Michelle. Thank you so much for your talk. I was interested to learn more about the data that are currently accessible to any member of the public. What can they download? And at what level of geographic specificity? Yeah, that's a good question. So we, we have a few mechanisms for people to access data. The easiest that doesn't require them interacting with us at all. Is they can download the current data that are shown on the COVID data tracker site. So all of those metrics at the sampling location level. We're not providing the names of the wastewater treatment plants themselves. We anonymize that. But it is whatever data is shown on that, on that dashboard is available for download. We also have two data repositories on a public data sharing site called data dot CDC dot gov. So the full history of what's being shown on COVID data tracker, including the smooth wastewater concentrations at the sampling site level are available for download there. And then we also have a public data request process where people can request much more detailed information. We still anonymize the wastewater treatment plant, but they can request the full, I think it's around 200 analytics variables that we have available, including the laboratory metadata, the wastewater infrastructure metadata. And I think we filled, fulfilled around 10 or 12 data requests to the state. Most of them have been academic researchers, but anybody in the public just has to sign a daily use agreement. And then we released that to them. All right, Rekha. Thank you, Joan, for a wonderful presentation. My question is kind of, I think you touched a little bit on that in your last slide when you were talking about future plans for a data trend. So on COVID data tracker, you are right now showing 15 day percent change trends. And some of the jurisdictions, they are not getting samples bi-weekly. They are still collecting once a week sample. So for those jurisdictions, we cannot see any data on COVID data tracker. There are gray bars, gray dots, and we get lots of questions from our community partners, our stakeholders, curious Virginians. They always ask why we don't have any data, you know, reporting or something like that. So are you planning to change that to something different so that you can accommodate all the jurisdictions? Yeah, we talked a lot about the time period that we wanted to represent data on. And with that percent change metric, we were really, we really wanted to make sure data were represented on a timely basis. So what's the most recent data we have? We, I think the biggest concern we have is if we show longer time periods, then what does someone do with that? If you're showing data from a month ago, like how informative is that, especially in a pandemic that can change so quickly? We are talking about in the third iteration to allow some date modification so you can select different time periods to look back over time, which would increase the amount of recent data available and so current metrics shown. But I really think part of why we focused on such a recent time period is really just to make sure that people are seeing up-to-date data, knowing what's going on in near real time in their communities and not showing data that are old that may be confusing, especially if we allowed the most recent sample for a location to be shown, there's a lot of confusion that could result there if that's a month and a half old and they're looking at data that are three days old. And so knowing what the most recent results are, we really just had to be pretty strict in enforcing the more recent data only to be shown. Hey, Zach, I'm just struggling back to the limit of detection problem or challenge that Amy brought up in her talk and I noticed in your talk how the LOD can affect some of this data interpretation, would you guys ever have interest in recommending a target LOD or LQ? I don't know if we'd make recommendations that probably I'm going to start talking over my skis here and probably best to have Rory or someone on our lab side answer that, but we do capture the limit of detection for the assays within our data and we consider that when we're doing analyses if something's below the limit of detection, which as you're alluding to can't be quite variable depending on the assay that's being used. I think once we are moving toward this digital platform, I think we're going to get to a better state where we can start putting those frameworks in place that do have minimal requirements, particularly as we're hoping to be able to have more comparable lab data in the future. There comes with the ability to have a lot more specifications, but I don't know if we're at that point now with the wide array of methods that some assays and some instruments just may not be able to achieve an ideal LOD or LQ that we would want to have. Neroj? Zach, I had a question kind of similar to what Christine asked, which is if these data were say a leading indicator of hospitalizations or debts rather than say just some cases, do you have a sense of like how sensitive or specific they are? So for example, if in an area I find debt spike, can I go back and see a red bar three weeks before that spike in debt and what is the fraction of times I would see a red bar or the other way around that I see a red bar, what is the chance that I'm going to see a spike in debts or hospitalizations three weeks from now? Yeah, the severe disease question is always the big million dollar one. I think the challenge with wastewater data are because it is healthcare agnostic and we can pick up symptomatic and asymptomatic cases. The challenge becomes parsing out what proportion of what you're detecting is from those who don't have symptoms, that they're less likely to seek care, that they're less likely to be hospitalized and die. So I think when we want to start thinking about can we project out severe disease, looking at variants or mutations of high consequence, so there's lots of talk about being able to look at mutations that may be able to escape treatments or may in the future have like vaccine escape. I think that's where we can start to look into severe disease, but I think when we just look at this pooled sample without understanding more about what the proportion of symptomatic versus asymptomatic cases, we can maybe use vaccine and vaccine coverage to serve as a bit of a proxy for protection, but even that sometimes is difficult to extrapolate out. It's certainly something we're talking about beginning to explore particularly as we're getting into sequencing as to whether we can use sequence data to inform the likelihood of what we're picking up to result in the severe disease that you're talking about. But just to clarify, is there any current analysis that shows that these data are good for predicting severe disease? Not a strong analysis that I've seen. We know that the time period is roughly a couple weeks to three weeks from spikes in wastewater to the representative spikes in cases. Most of that is just the correlation to case spikes and then it takes a little bit longer, typically about a week or so for those people to start showing up in the hospital. But I know I haven't, but I'm not sure if others have begun to investigate whether there's that representative spike in that severe disease component of hospitalization and death that we're seeing in wastewater. It's certainly one of the things that we're starting to look at as we're identifying these meaningful thresholds and as we look back, I think we're going to start to evaluate things like that to see if there are those correlates with these severe disease. Thank you. Lauren. Hey, Zach. I wanted to talk about specifically one of our tasks is to discuss broad approaches to increase the public health impact of wastewater surveillance. And when I was thinking about your talk, you mentioned briefly about sampling. And I wanted to, I guess, get your thoughts on both the temporal frequency and variation in sampling by space. We've seen papers out there that indicate, you know, if it's a vulnerable community and we don't have really good indicator data for them, maybe those are places that we should sample more frequently than, say, a community that has, you know, well established, either the vaccine race, like you just mentioned, or our good syndromic surveillance or essence data. We really kind of know what's going on in a community. Maybe we could take our resources because, you know, we have only so much funding. And step back on the communities that we really understand and sample them at some frequency. And if we see something happening in one of these vulnerable communities, we step it up, you know, maybe trigger something. Is that something that you're thinking about? I don't know if it's something we've explicitly thought about scaling based on need. I know we certainly are being very intentional with this commercial contract to talk, to try and focus on more vulnerable communities. So two of the factors we considered when we were identifying priority sites, we're looking at counties with lower vaccination coverage. And then we also looked at CDC's social vulnerability index to see if we could make sure we had really good representative coverage of those communities, like you're saying, that are more likely to be impacted by increasing COVID transmission. I think it's certainly worth considering, particularly with upstream sampling, when maybe a community is looking at doing central testing more frequently at the plant, and then as pockets of disease or maybe being identified or there's concern that pockets of disease may not be captured as well with other indicators, we can think about upstream sampling. I know you all in Houston do lots of smaller scale sampling throughout your city to make sure that you have adequate coverage. And so it seems like a combination of the two might be helpful, looking at both just traditional surveillance coverage, access to healthcare, and then what the vulnerabilities may be in those communities to help prioritize where the sampling occurs. I think what's really important though is just the duration and consistency of sampling. If you don't have that historic perspective, it can be challenging sometimes to know if what you're seeing is a meaningful trend or if it's just an artifact because you just started sampling there and you don't really have a good grasp on what the baseline levels are, especially as we start thinking about what COVID gonna become just an endemic disease and we have a better handling on what typical expected levels might be. Right, so I just had this really quick follow up on sneaking in. Have you, when you, so it sounds like you have a lot of data where there are people reporting on the weekly basis and then you have ones that are reporting twice a week and have you done a cross-validation where you can see like, was there like a great impact of the two times a week versus the one? I think we landed on the twice weekly because we found it has, there's better responsiveness to the data and that's why we've encouraged twice weekly sampling just because with most of our measurements they're either time or measurement based. So obviously the more frequently you're sampling, the more frequently you can have new trends that also can introduce additional noise. So we felt really honing in on twice weekly sampling gave a good balance of not only sensitivity of the assays and the system but also it was not overwhelming for the utility operators. They're completely new to public health surveillance and so keeping in mind their capacities and willingness to participate not burn them out was also a consideration. So we don't have any great data on within a site if they've changed different sampling frequencies of whether or not it improves resolution of what's going on. But I think that's a really interesting evaluation that maybe some of our centers of excellence or other groups that we're looking to fund in the next cycle can start to investigate. All right, Christa, last question. Okay, hi, thank you so much for talking and I'm just going to build on this resolution question on the public facing website. You know, is there, does it currently show how many data points have gone into those trends? Because I'm thinking, you know, the people who look at the website might trust a trend more if it's based on daily samples as opposed to weekly or bi-weekly. Is there a way to, do you show that and if not, why not? We don't yet. It's something that we need to, particularly as we're showing percent change because sometimes a location represents two samples over that 15-day period and others represent as many as like 10. And so that's something that we're going to probably be adding in the next round is that and also showing the most recent sample date just so it's clear of when in that 15-day period the most recent sample was collected. All right, thank you. And thank you again, Zach. We're now going to break into one o'clock Eastern time and then we'll reconvene. So thank you all of the presenters this morning. It's very, very, very helpful. Right. Welcome back everyone. We're next going to hear from several of our speakers around some of the challenges and concerns regarding implementing a national wastewater surveillance system. Before I introduce my first speaker, our first speaker, I also want to give Marissa the chance to introduce herself. She's just joined us. She's a committee member, Marissa. Hi. There you go. Okay. There we go. Better. All right. So yeah, hi, I just wanted to say hello. I'm a faculty at the University of Michigan in epidemiology and complex systems. And I don't know how much introduction I'm just to get. Is that the whole deal or more? I do a lot of work on mathematical modeling, including of infectious diseases, but also of wastewater surveillance and that kind of thing. And I've, I've worked on polio and COVID with wastewater. And yeah, that's, that's the, there we go. Perfect. Perfect. All right. Thank you very much. Yes. I want to introduce Nathan lacrosse. He's with the Utah department of health. And he's going to speak to us about the opportunities and limitations of syndromic versus wastewater disease surveillance data. So Nathan. Hello. Thank you. Hopefully everybody can hear me. Appreciate the invitation to speak. So I'm going to be talking a bit, as Guy mentioned about wastewater surveillance, a little bit about syndromic surveillance. I manage our wastewater surveillance program. I'm not an expert in syndromic surveillance, although we do have some very, I think, fruitful and encouraging collaborations with our syndromic surveillance program on going that I can speak to. So I'll get. Let's see. Too far. There we go. Okay. Just a little lag. So very briefly, I want to describe what we're actually talking about with wastewater surveillance and syndromic surveillance, wastewater surveillance. Amy Rachel and Zach did a great job of introducing a lot of the concepts. So I won't spend too much time on that. And I do want to mention that the points I'm going to be talking about are going to be related to the systems and data we have in place in Utah. They're going to be different in other areas, of course, naturally speaking. So with wastewater surveillance, as has already been mentioned, we're largely talking about community level surveillance, although it certainly can be done at different levels down to single buildings, potentially, really anywhere you can sample. In Utah, currently it's all community level surveillance of quite a wide ranges of community sizes. The data and samples typically they're collected new. You're not making use of existing data, although with a caveat that whenever possible, it's good in my opinion to try to piggyback on existing sampling schedules that the partner facilities are already conducting just to ease the burden, streamline things, make things even more efficient. But typically this is new data. They're new samples. It's not something that already exists. You're collecting it for this purpose. And the Turner on time varies. You know, Zach gave some national perspectives in Utah for us. It's typically in the neighborhood of two to three business days between the end of the sample collection period. And when we actually have the data in our hands, which is pretty good. I think there's not much we can do to really reduce that down too much. So drama surveillance, rather different, of course, this is typically something that is hospital health care related. What specifically it is can vary quite widely in Utah. We're specifically talking about emergency department visit related data. So just emergency departments. These data are already being collected typically for at the very least the hospital health care facilities own purposes for their own internal reporting purposes, building purposes, that sort of thing. And you can make use of quite a different variety of data that comes out of those facilities. Again, in Utah, we're specifically talking about typically some combination of chief complaint and initial discharge diagnosis data. Most of our systems for syndrome surveillance make use of both of those for COVID specifically. It's the initial discharge diagnosis just because chief complaint. There's too much crossover between influenza and RSP that to be terribly useful. And in Utah, again, this is what I've experienced with here. There's typically a lag of around three days for most data to enter our system, although some of it does trickle in as time goes on. However, most of the analyses make use of. Averages over a period, often a week or seven day averages. And so the time between. Some event occurring, and then you being able to see that change in these averages is more along the lines of somewhere around a week to a week and a half thereabouts. And then the maps are just on the left of map of our currently sampled wastewater facilities with 32. And a map of the emergency departments that are part of their syndrome surreal system, which is 49, which is all of them, which is great. Then. So want to advance. There we go. So briefly strengths and limitations like all data systems, surveillance systems. Each has their own set of strengths and limitations. I think the takeaway to put that first is that in a lot of situations, these are really complimentary systems and that they can be used to strengthen each other there. One strength can help overcome other's weaknesses and vice versa. I don't really see much conflict between the two. I don't see much conflict between the two. I don't see much conflict between the two. I don't see much conflict between the two. And again, these have really been covered. Very, very well by our wonderful CDC presenters earlier. So that move pretty quick here. They are very independent of traditional public health data sources, things like access to testing and healthcare seeking behavior. I know Amy mentioned this as a really important point. I completely agree. I don't. I think this is something we knew going into this. And it's something that has become. It's really important to include, to include the changes in individual level testing in recent weeks. It also captures all shedders, including asymptomatic cases. Now, not all people will shed necessarily, but everybody who does, we're going to get data from them, which is really important. So it's not dependent on people being symptomatic or their severity of their symptoms. It's also very efficient. We are currently sampling. At these 32 facilities statewide twice per week. twice per week, and that covers about 88% of our state's population. And that's just not something that's feasible with individual level testing. It's just not something that could be done, but we're able to do it sustainably and consistently. And as also been mentioned, there are inherently pooled samples. And I kind of put this in the middle of a little bit of extra gap, just because I think it's, it can be both a strength and a limitation, depending on what you're trying to do. So if what you want is to get data about a given community in your sewer shed, your wastewater service area, reasonably covers that community, then great, your sample's already there. You don't, there's nothing else you need to do. That being said, if you want to get more granular, you can't do that with that type of sample. You need to get a different sample, typically from a different sampling point or a different sampling area, because you can't unpool it. It's inherently pooled. Some of the limitations, there are a lot of unknowns. There's a lot of things we don't know, a lot of very open questions, especially the research side, I think. And the data can be quite volatile, but you can see quite a bit of variability in the data. And it's not wholly clear all the time whether these are reflecting actual changes in the community that we might want to know about and pay attention to, or whether it just represents changes in the wastewater stream, changes in temperature, weather, storm events, something like that, that changes our data, but it's not something that is of public health interest. And that could be difficult to deal with. And as Zach mentioned, and this is also very, very true, there's a need to establish a certain amount of baseline data, so you know what data from at its site looks like, and you can start determining what it might mean, because each site has enough unique factors that you can't necessarily take conclusions and thresholds and metrics directly from another site and apply them to a new one. A lot of times, it's just not going to be valid. And so you need to collect data over enough period of time, so that you start having an idea of what you're actually looking at and talking about. It could be quite difficult to aggregate and compare data between sites because of all those differences. And in a lot of situations, best practices haven't really fully emerged yet. I think this is changing over time, thankfully, as people get more experience and we try to do methods, we start figuring out which ones are working even better, which offer more advantages and other methods. But it's a new area, it's a new science, and so we're still figuring things out. And as also been mentioned, septic use can be an issue more so in some areas of the country than others in Utah, a lot of the infrastructure is relatively new. So our septic use is on the lower end in other areas with older infrastructure, especially on the east coast or the Midwest, that can be a significant problem. With syndromic surveillance, it's also independent of testing, which again, extremely, extremely valuable, especially in times like now. The status of individual testing really doesn't bear much influence on the data you get out of this system. And it's also a mature system with really well established methods. And this is very valuable, especially on the wastewater side, as we're trying to figure out some of these best practices. And we're hoping to be able to take some of the experiences and methods and lessons learned from syndromic surveillance and apply them to our systems. And it's already, it's very efficient, very similar in many ways to wastewater surveillance, because especially because the data are already being collected for the most part. So it's just getting that data and getting it into the system and databases where you can make use of it for public health purposes. But typically it doesn't involve collecting any new data, it's just getting the data to where it needs to be. And it's really individual level data still. So aggregation is relatively easy. You can do it like you would aggregate most other individual local data. So if you want countywide, statewide, what have you, that's really typically not too much of a problem. And in fact, like most individual level data sources, the greater the geographic scale you aggregate on, typically the cleaner and a little bit easier to deal with the data becomes as well. Very different from wastewater surveillance in that regard. Some limitations, it is inherently, of course, extremely dependent on things like access to healthcare and healthcare seeking behavior. And these things are not evenly distributed and access and seeking behavior are not equal across all populations, all communities and all groups. And this can be a real problem. And this is one that's tough to solve too, because it gets down to the root of issues with our healthcare system. And it can be very dependent on symptom severity. So these are people who had symptoms severe enough or some other issue that was severe enough that they actually presented to an emergency department, depending on which disease we're talking about, which variant we're talking about, that may not be most of the people. That doesn't mean it can't be useful. Oftentimes the trends will still remain the same. But it's important to keep that distinction in mind. And there's a trade-off between timeliness and accuracy when we're using things like the initial discharge diagnosis. You can wait for more accurate and refined data to come in. But again, you've lost that timeless, you're often waiting weeks, if not months to get that more refined data, which is great retrospectively. But when you need to make a decision now, it's not so helpful. So as I mentioned, I really ultimately, I think that these two surveillance systems are very complementary. They help strengthen each other. I don't, thus far we haven't had any conflicts between the two. And I don't necessarily foresee that in the future. I think if, even if the two systems are to show very different things, that's more likely to reflect actual differences in what they're measuring because they're measuring different points in the progress of an infection between shedding and having severe enough symptoms that you're going to the emergency department. They're measuring different things. I think it's likely to reflect real things that we want to pay attention to and would be of interest and not just artifacts of the type of system we're talking about. But we'll see as time goes on. And last slide, I want to talk a little bit about some of this very preliminary, very rough to put it mildly data we've been working on and systems we've been working on integrating these two data sources. So we have an ongoing collaboration, as I mentioned with CDC and with our syndromic surveillance folks here at state to try to find ways, commonalities, ways to bridge some of these gaps and to make use of a lot of the knowledge and methods that syndromic surveillance has developed over the years and apply them to our data and coming up with ways that we can combine these data to make them both even stronger. And so this is some work we've been also doing as a side project of that to help develop some readiness metrics for hospitals, so statewide metrics, hence the need to aggregate the data to statewide level. And it can be quite complicated wastewater has an inherent geographic scale is that covered us I think quite well where each site is unique enough that it becomes quite difficult to compare and aggregate data between them. So at that community level, it's great broader, it becomes more difficult, syndromic it's it's there's a different story it's a little bit easier there. And that's what I mean by each word best at different aggregation levels really thus far wastewater level works best quote unquote at no aggregation but a lot of times aggregation is necessary. So what we have here are two charts the top one is wastewater data the bottom one is syndromic surveillance data so emergency apartment visit data the on the top chart the blue and orange bar chart of the statewide daily case counts and then the or the red line are the number of sites with levels above a certain quantile threshold. So this is very much like those heat maps that Zach was showing the fact based on the same methods where we got I got the idea and just taking all the data from a site dividing it into essentially straight quintile thresholds bins and then finding which ones are at that 60% plus bin and counting the number of sites per day and it actually works surprisingly well as an indicator and even predictor of when we are going to see these surges in covid cases as you can see and in the bottom chart these are roughly lined up on the time scale on the x axis by the way is the syndromic surveillance data over a similar timeframe showing the percent of emergency department visits with thresholds at blue being less than 4% or relatively low for one definition of cases due to or severe cases due to covid that yellow is between 4 to 6% so sort of a middle ground and then the orangish pinkish reddish is greater than 6% or high community levels there and you can see very similar things so they can both work really well as indicators and predictors of changes in what we're what we would see in individual level cases even when we wouldn't have that data like now potentially and I think they can work really well in tandem too and provide more strength because if there's great value in having multiple independent data sources and if they're both showing you the same thing that's I think much stronger evidence and more stronger rationale for taking public health action than just relying on a single data source and that is what I have I would be happy to take your questions. I think we're gonna hold the questions until the presenters because I think there's gonna be some crossover and I think the questions then can be directed best at that point but thank you very much Nathan that was an excellent presentation. Next I'd like to introduce Jose Romero and Mike Sema from the Arkansas Department of Health bring their slides up. We don't have any slides we're going to just present our limited information. Thank you very much. I'm Jose Romero I'm the Arkansas Secretary of Health and the Director of the Health Department. I'm also a professor of Pediatrics, Pediatric Infectious Disease at the Medical Center and we're this is really our presentation is more about I think the adage bringing coal to Newcastle fits with this presentation because a lot of what we're telling you you already know so we are a rural state our population is about three million people and we have three wastewater sites currently functioning these are in small communities one of 1600 people the other one of 16,000 people one of these sites actually has two wastewater sites that are contributing to CDC data we submitted 13 proposals and only have those three on boarded at this time so 10 are not on boarded so the speed with which was talked about and again was talked about about getting these up these sites up did not really apply to Arkansas and let me just also preface with this I'm a big proponent of wastewater surveillance and I think it has a utility in a number of diseases not just what we're talking about which is COVID but I'll talk about that in a minute so my comments are not to detract from that they're simply to bring to light certain issues that we view here as a rural state so it's important to note that for our systems our wastewater systems many of these are very old and they're open systems they're not closed systems and they are diluted by rainwater or runoff during certain times of the year and that is going to be an issue that I think we will encounter as you begin to move into rural states and states that do not have these well-defined municipal water treatment systems it's also important to keep in mind that about 1.1 million of our population so about one third of our population is not linked to a municipal wastewater site they have septic tanks and they would not be captured in a surveillance system now the argument could be made that well some of those individuals will be working in town for example and therefore you'll catch you know their their their refuse that way but but but bear that in mind also note that in my state that is in Arkansas the site that has or the region of the state that has the lowest number of these wastewater treatment facilities and and the highest number of of of these home sites septic tanks is located in the southwest corner of the state that is sorry the southeast corner of the state the delta and that is the poorest portion of our state and therefore as you've already talked about this issue of disparity and and equity in in surveillance so that group of individuals may be disenfranchised by focusing on these large wastewater systems for surveillance and we and I bring that to your attention only um we also view other things such as cost so the cost to get this started um is significant now we invested significant amounts of money for nucleic acid amplification testing for COVID and we can do genomic sequencing now within our system that's our public health lab we agree fully that the public health lab should be the lab to to to perform these uh in in the state but there will be an outlay for concentrating the specimen for for nucleic acid extraction from these from these uh from these samples further COVID has really taxed our public health lab we are limited in space we had to expand dramatically in order to put into place systems to make to diagnose uh uh COVID rapidly within our state and so our health department lab literally has no space where to put these this this project now we're lucky um we've thought of a way of doing this and and we're going to employ a modular system that we currently have on site so um we we we think we can get this started I'll talk about that in a minute and lastly the issue of distrust may be very significant so in states like mine there is a significant distrust and loss of loss of confidence uh with the public health system and in particular with the CDC something that I hear continuously from our legislators and the legislators have taken an active role in in in the um in the regulation of public health in our state um you know we have we have mass mandates uh or really against mass mass use against use of vaccines so in some states it if there is a perceived um issue with security of personal data from this you could see uh in my opinion um a movement from the legislators to limit the ability of this use of this data that being said I think that this has a great future and let me let me give you two examples that I think are very important firstly an act a problem that we now have in the United States we have resurgence of tuberculosis we have had an a cluster of TB arising from arising from the COVID pandemic where they were not seeking care and that cluster was significant if we were able to surveil wastewater and find these genomes in the wastewater we could implement a contact tracing or active surveillance for TB in those sites another area that I think uh is going to be very important is in polio virus surveillance I'm I'm the chair of the national certification committee for uh for polio eradication we report to the to pacho who in turn reports to world health organization as you know or you may know there have been now outbreaks of wild type polio in Malawi and circulating polio virus in other countries so this is a threat to the US and it we do not have an active surveillance system for this at this time all this to say that I think that there is a great future for this we just need to figure out how to roll it out and I will turn this over to Mike Sima for his for his comments Mike I think you're muted can you all hear me okay sorry about that I have no idea between this morning and today but I will keep my comments very brief I I do want to thank you all for the opportunity to participate today I think first and foremost you know I've learned more today about the national wastewater surveillance efforts than I have in the past year or two combined which you know I appreciate but it's simultaneously a little bit concerning you know it's clear that there's much more information out there that just simply hasn't diffused down to states like ours and I think that we're missing an opportunity to use a powerful public health tool and I think if you know wastewater is going to be a successful endeavor at a national level that the connection with rural states localities like that in Arkansas needs to be much stronger and there's obvious avenues for those types of connections namely through ELC which we are going to be participating in but it does seem that we have you know we're jumping in at square one whereas others may have had you know early opportunities to be early adopters and I like most of my colleagues like to have the opportunity to be pioneers in the public health practice in science arenas. Other than that I thought Jack did a great job clearing up a lot of questions that I personally had about the data analysis component and you know I don't want to be too repetitive but it seems that it is clear that a more standard approach to trend classification in particular is needed you know percent change in relative levels are moderately useful metrics but it has been pointed out numerous times already percent change is flawed that it can be unclear what the actual practical importance of fluctuations are without more context and even for the relative levels which I believe is a relatively new metric to make its way onto the COVID data tracker it's not clear to me what impact of any that you know historical levels after a monster wave like Omicron are going to have on that particular measure for sites that have been you know monitoring voice bars SARS-CoV-2 for extended periods of time it seems that if we're relating things back to you know Omicron levels that we're going to miss early fluctuations and and levels at those particular sites and then you know obviously you know further downstream the considerations that are required for you know state and health departments local health departments to integrate wastewater surveillance into their actual public health response and and actually operationalize this information that we are getting from this novel tool so that we're acting appropriately you know it's it's clear that wastewater surveillance is going to give us an opportunity to detect aberrations much much quicker than you know what we have previously done in order to you know fully make or to make you know full use of that utility you know really having a concerted effort early on as we on board further targets for wastewater surveillance to give consideration to what an appropriate response is for fluctuations and wastewater levels for particular targets so that's something that we will be considering as we initiate and expand wastewater surveillance here in Arkansas and that's all I really wanted to add to the conversation today. Thank you Jose and Mike thank both of you. Next we're going to hear from Anna Merotra from the Water Environment Federation for Perspectives about small and mid-sized utilities in implementing and expanding wastewater surveillance systems. Great thank you all it's a it's a pleasure to be with you all today and I wanted to talk to you really about two ideas like I guess I'm gotta figure out how to forward the slides. Okay two topics that I wanted to cover with you today some definitions and numbers related to small and mid-sized utilities and then I want to offer up three considerations related to engaging these utilities in ongoing wastewater surveillance programs and I'm calling these considerations the three P's permit people and point one of the big takeaway messages I hope you come away with is that there are many and many different types of small and mid-sized utilities in the US and one way I want to convey this is by showing you a series of Google Earth images for smaller facilities that are currently engaged in or have been engaged in wastewater surveillance programs so this is your first example on the screen here a conventional activated sledge plant from upstate New York. Okay so let's start with definitions how do we define the size of a wastewater system or a utility so this is typically done either on a population basis or a flow basis and this flow can either be permitted capacity or it could be the actual flow usually represented as the average daily flow which is the average volume of water that that wastewater facility treats during the course of a 24-hour period. So EPA defines a small wastewater system as one that serves less than or equal to 10,000 people and has an ADF of less than one million gallons per day or less than one MGD and I'm essentially going to use the same definition but there is no definition for mid-size and so I'm going to go ahead and invent one today for our purposes and say that a mid-size or medium wastewater system is one that has a permitted flow capacity of more than one MGD so it's not small but it's the capacity is less than or equal to 10 MGD and you'll note that I'm using the terms wastewater system and wastewater utility sort of synonymously and that's okay for small and mid-size utilities where there's typically one wastewater treatment plant one wastewater system for that utility that kind of falls apart when you get to larger utilities that will have multiple wastewater systems under their umbrella. It's worth noting of course that permitted flow and ADF are not the same thing but they're closer than they are not close. You know a plant that's permitted for a million gallons per day is not going to be reporting an ADF of a billion gallons per day. It's also true that ADF is proportional to the population served but things like climate, water use, the age of the collection system those things really complicate that relationship more than you think. Okay so let's talk numbers. So based on WEF data that we take from permit information available from a variety of sources we think that there are about 15,400 permitted water resource recovery facilities or WORFs in the U.S. These are wastewater systems that largely treat municipal sanitary flows sewage but also can treat other flows you know industrial industrial flows and the like. Of these these facilities we have permitted flow capacity information for about 12,500. We also have ADF information for some of these but it's about half as many as that 12,000 number and here I'm showing you another example of this time a mid-sized facility that's all bundled up inside buildings in Alaska. Okay so let's dive deeper into the numbers. If we divide up that 12,500 or so WORFs 12,442 to be exact for which we have permitted flow capacity data into five bins so there are five colors on this pie chart and I'm using extra large to correspond to plants that have capacities greater than 100 mgd. Large is something that's more than 10 but less than or equal to 100 medium I already defined one to less than or equal to 10 and then small is anything less than or equal to one mgd. Again this is permitted flow capacity and I actually further divided small into an extra small category so each you know piece of pie over here just corresponds to the number of these facilities that fall into that bin and what you can see is that the small and the extra small you know account for the the majority of the number of WORFs in our in our country. It's a different story of course if you count up total permitted flow and for each of these bins so on the right hand side now I'm showing total permitted flow is relates to the size of the pie piece instead of total number of facilities and in this case you can see that the large and the extra large account for most of the permitted flow. In other words well less than half a percent of all WORFs represent about a third of the total permitted flow capacity in this country but more than 90 percent of the WORFs so that's all those that fall into the extra small small and medium categories represent about a quarter of the permitted flow and we can extend this analysis to population served instead of permitted flow but you get the idea and there are a lot of small and mid-sized facilities in the U.S. and I should note that around 7,000 of these extra small small and medium facilities are lagoon systems and I'm showing an example here on the right from North Dakota and also behind me too. All right so that brings me to the three considerations that I want to offer up when thinking about sustainable participation by small and mid-sized utilities so the three piece and the first is that meeting its permit requirements is any WORFs primary mission. The second is that having enough people at the WORF is a prerequisite to wastewater surveillance program participation and the third is that being able to see the point of participating is a necessary condition for sustained program participation so I'm going to go into each of these a little bit more but here's another small utility that's currently participating in a wastewater surveillance program in Massachusetts. Okay so let's talk about permits first and by permits I mean national pollutant discharge elimination system or NPDES or NIPDES permits and when it comes to permits it's important to keep in mind that permits are largely written whether they're written by EPA or by a delegated state agency around effluent requirements so this is an excerpt of a draft permit there's just an example from a facility in New York and you can see that this facility has effluent limitations related to for example total suspended solids you know they need to achieve 30 milligrams per liter and 87.57 pounds per day of TSS on an average monthly basis again that's based on the effluent and they need to demonstrate compliance with this limit by collecting composite samples of that effluent once every two weeks and so this is all about the effluent wastewater surveillance of course focuses on the influent and ideally more frequent sample collection than twice per month and most of the time permits oops are not written to directly address influent sampling requirements so it is all permits are based on meeting the requirements in 40 CFR port part 133 this is the secondary treatment regulation which requires there are some exceptions to this but which requires that a facility achieve secondary treatment which is defined as 85% BOD and TSS removal across the facility so to calculate that you need to know what's coming in as well as what's going out however influent sampling type and frequency are not necessarily specified in the permit there are exceptions however some states do include influent sampling requirements on their permits Iowa is one example Kentucky is another example and here's just a snapshot from an Iowa Nipides permit showing that there is monitoring specifically required in the influent this is all just is just to give you an idea and that a worth needs to sample for permit compliance first and wastewater surveillance or some other goals second and the permit sampling routine may not be compatible with the needs for wastewater surveillance sampling especially at smaller facilities where permits we require you know less frequent sampling okay so the second P is people and it goes without saying right that people are needed to collect samples at worst and and at smaller facilities these people are often certified operators because a small facility might not have laboratory staff and the laboratory staff might be doing the collection at larger utilities so good data on the total number of licensed wastewater operators are hard to come by one estimate is 20 000 which would work out to be a little bit more than one operator per wharf we know that there are some wharfs that have many more than one operator and there are some that are staffed by one part-time operator and this may be especially and that part-time operator may be remote or it may be a full-time operator that's remote this is especially the case at the that thousands of lagoon systems that I mentioned in the US although it was not the case that this lagoon system I'm showing here this is one from Wyoming that participated in the state-run surveillance program through the end of the year and is actually staffed by three operators it's quite a large system you know it's notable that insufficient staffing or resources but mostly staffing was the third most common reason cited by wharfs for not participating in the first of the phase three commercial testing contracts okay so staying on the topic of people um having what I call a wastewater surveillance champion can make all the difference and I've been really lucky to be able to um sorry about that um I've been really lucky to be able to talk to many of these champions you know Philip from Wyoming Kerry from Alaska um Crystal from Oregon these and many many other wastewater utility staff are people who feel that supporting wastewater surveillance programs is the right thing to do um but it's critical to view wharfs as valued partners in this pro in these programs and you know not make the assumptions that the Phillips and the carries and the crystals will always be there to support wastewater surveillance efforts and this is where incentives can help and when I when I mean what I mean by incentives it could be many things it could be paying stipends and bonuses um providing courier services uh supporting operator training or licensing requirements reimbursing the purchase of auto samplers or flow meters uh helping map sewer sheds and we have a lot of work to do in terms of figuring out which incentives are most highly valued by wharfs and how best to implement incentive programs but you know making a clear and material demonstration that utilities are valued partners and wastewater surveillance programs is absolutely imperative um and finally uh along the lines of demonstrating that utilities are valued partners um you know all utilities really all of us frankly right want to see the point of what we're doing we want to understand uh how this technology will be valuable beyond COVID and I would say that utilities really do want to be they want to see the data they want to see the data in a timely manner their wastewater data you know they want they want to get the data right from the lab and they don't necessarily want it to go through a health department partner um so with that I'll um turn it back over and uh look forward to the q and a thank you very much Anna um our last speaker is Lance Gable from Wayne State University who will speak to the ethical and legal considerations for wastewater-based disease surveillance and after his presentation we'll have time for for questions well thank you everybody it's a really great pleasure to be here as part of this committee today to get to uh to speak with all of you and to uh to share some ideas um I want to acknowledge at the outset um two colleagues who've worked with me on a lot of the developing of these ideas um Jeffrey Ram here at Wayne State University in the medical school who's an expert in in wastewater surveillance and Natalie Ram a professor at the University of Maryland's law school who's an expert in privacy law and we we've been working on these issues since early in the pandemic initially along with some of my colleagues we were looking at doing some wastewater screening on the campus in the very earliest parts of the pandemic before the national programs and the broader initiatives had started and we began to think about a lot of the legal and ethical issues that were inherent to this kind of work and started to develop some ideas around that and then later on now we're currently participating with NWSS and with the the state and local health departments here in Michigan to to actually participate in the in the surveillance projects that are ongoing here in Detroit um I think you know since so many of actually let me make sure I can oh there we go I've got it moving um so so obviously the the the incredibly rapid expansion of the systems presents some really important opportunities for public health um and creates the the kind of capacity uh that that would previously have not been really I think conceivable had it not been for for this great investment of resources and I think um when you have a significant expansion of a new system like this for a public health purpose um you know it creates these great opportunities but it also creates um the need to think really carefully about what the downstream uses and and potential future uses of these systems could be both for the good and both and and also for thinking about how they could be potentially used in ways that could raise ethical concerns and and could could invoke some some legal concerns as well and so I I think where we start is if we're looking at you know and I'm not going to go through the the in detail uh some of the potential uses of this of the information gathered through these systems because I think that's been covered really well by some of the other speakers today but I think some of the proposed uses for wastewater surveillance are fairly straightforward you know public health surveillance uh techniques that and they fit clearly within the well established rubric of public health surveillance that is easily supportable under existing law is easily supported under existing ethical um analyses of public health um you know the using this information again um uh now that we we've gathered enough information to know that there there is some credible scientific basis for linking SARS-CoV-2 detection to the potential for future spikes in in uh in COVID cases in the communities where the detection occurs you know that kind of you know public health opportunity to add this this technique to the to the toolkit of screening for disease um and and serving as an early warning sign complimenting other surveillance efforts that are ongoing uh is really very promising in lots of ways but but I think you know some of the other proposed uses especially when we talk about using some of these data in a more targeted more granular way um there I think you know we need to think carefully about how that information is used once it's collected in particular it can be used in a very positive for very positive public health initiatives like targeting resources towards communities that are at greater risk and and to really direct resources rapidly to those communities when outbreaks occur uh on the other hand um sometimes you know collecting this data at that more granular granular level can be more likely to implicate privacy concerns and the potential for discrimination or stigma against people in communities that that that end up testing positive for new outbreaks and so and and and especially as we move beyond the the COVID focus uh SARS-CoV-2 focus of these screening systems we need to keep those kinds of of potential concerns especially foremost in our minds I also think that um uh you know this this list of uses is certainly not comprehensive and there are a lot of things that we've already even talked about today that go beyond this list that also have different kinds of implications and so you know using data collected through wastewater screening for targeting resources um can be a role public health positive um but if if that's the only tool that's being used or it's one of the primary tools being used to target resources and you're not targeting resources towards other areas that might not fall within these systems that might might be invisible to these systems that's something that needs to be kept in mind as as as we go forward now um I wanted to earlier on um during during Rachel West's presentation she identified a number of ethical considerations and and I want to kind of build on some of what she was saying earlier on um you know the there's there is some really good work out there that started to look at some of these issues in detail the the WHO uh public health surveillance ethical guidelines are really useful I think as as are the the guidelines developed by the Canadian Water Network um and I think we can focus on kind of a couple of very broad types of ethical considerations and thinking about conducting wastewater surveillance um among the considerations um one is the focus on the common good and so when surveillance public health surveillance systems are being developed we want the systems to develop with the goal of trying to advance a clear and legitimate public health purpose and making sure that the analysis use and dissemination of data collected through these systems um corresponds to that uh that public health purpose um one one thing that I think is you know one potential risk of uh the the existence of these systems in the longer term you know that they have a great potential to be used for lots of different types of things and you know keeping the focus on that those public health common good purposes where where this data can be utilized and making sure that there's not a mission creep over time where you know people realize these systems are available and want to use them for other purposes that are not necessarily uh going towards uh trying to improve public health and we also you know of course make sure that the data being collected and being used and justifying these public health interventions are valid data and of high quality and and advancing those goals um on the point of ensuring equity this is essentially important so um uh in a just society we need to take steps to allow everyone to flourish even in the face of social inequity and disparate access to resources and this goes to some of the points that I referred to earlier so if we want a justice oriented equity oriented wastewater surveillance system we want to make sure that the the system is not being used in ways that imposes additional unnecessary burdens on populations that are more vulnerable and take steps to reduce these burdens that already exist and so this could this could include in some circumstances refraining from the release of data that generates discrimination or stigma towards people in a particular community especially it's targeted toward a particular community um but on the other hand it could mean that it's an imperative to release data so that people have access to information that they need to take to to allow them to protect themselves against risks that are that are currently emerging in their communities the the data can be used to um to bring resources to to areas that need them by targeting uh areas that are most at risk but equity can also be undermined if the systems instead result in disproportionate application of restrictive measures against those communities compared with non-surveyed communities and so these these are a complicated set of considerations but these need to be part of the the process in analyzing how data should be used and just to give one example um you know focusing surveillance for COVID for SARS-CoV-2 on university campuses might have the effect of concentrating resources on a population that might be less vulnerable um to COVID-19 and reducing equity allocation of resources to other communities that might not receive that attention um and similarly excluding systems that are not connected to sewers or municipal systems could also lead to that same type of result um respect for persons is is a core ethical consideration as well it's important to remember that uh or to to make sure that public health surveillance um is being done in a way that keeps in mind the effects of of these systems and the information gathered on individuals and if you know that i'm going to talk in a few minutes about privacy considerations but there could be implications for privacy autonomy bodily integrity individual rights etc depending on how information is used and so if if detection of a positive wastewater signal for a disease outbreak occurs um there has to be some consideration of what that information is used for if these are target resources that's a positive public health benefit if it's used to to immediately impose serious restrictions on a targeted area that might be public might be supported by the public health goal but it might not be and so um thinking carefully about how information is used to downstream justify certain kinds of interventions as part of this this calculation and then as if the sampling area has become smaller and smaller more granular data being collected and uh if genetic sequencing and other techniques are being used that i can identify individuals that also raises some concern about privacy violations as well and then and then finally here um enabling good governance um having transparency developing trust among communities um is an important aspect of thinking about how these systems are going to operate and so this includes um having good safety protocols um data sharing and retention policies uses policies about use of data to spur other kinds of public health measures um and a lot of other issues as well and so um but also obtaining community ascent and community understanding is really important to ensuring that in the long-term communities will support these initiatives and be on board for um the consequences that come from gathering data through these systems um uh one of one of the points that that Jose Romero made in his comments a few minutes ago I think was really um uh especially important that you may have and this kind of goes to the the last slide I have here that I want to show which is um everything about legal implications you know who has the authority to to conduct surveillance generally public health surveillance authority is fairly broad state and local governments have a broad degree of of police power authority to engage in these kinds of activities but if there's a loss of community trust or a loss of trust among leaders who see these systems as um invasive or problematic that could lead to efforts to try to undermine the authority to conduct these kinds of surveillance efforts um also need to pay attention to the scope of surveillance making sure that it's focused on public health purposes and the data being collected are not being used for um additional non-public health purposes that could that could also give rise to legal challenge and could give rise to really problematic mission creep um one example here of course is that if data is being used um for to to uh for example to target people through law enforcement um I I know infectious disease surveillance is unlikely to lead to this kind of use but if we're talking about screening for drug use and screening for other kinds of substances in wastewater it could give rise to a lot of other potentially problematic uses and there is some legal precedent that would limit law enforcement being able to use these kinds of systems uh you know fourth amendment protections that require um you know the the the court to get a warrant and probable cause to conduct a search however um the this is something that we need to keep an eye on again as the the system is grows and expands we can also imagine other kinds of entities wanting to get this information for non-public health purposes you know life insurers might be really interested to know the communities where there's a higher incidence of metabolic factors in the wastewater associated with chronic diseases and so um thinking about not only what we're planning to use the system for now but what some of the long-term implications can be and so I know I'm running out of time and I'm just going to sum up by saying that you know this these systems present such an important opportunity to expand public health surveillance in a way that can really benefit our communities in some substantial ways and um but as we're developing these systems we need to keep these legal and ethical considerations in mind needs and many others and ensure that as these systems evolve they're being developed in a way that that takes these factors into account and maintains public trust thank you thank you lance and and and thank all of the speakers those those were really fantastic presentations and I'm sure our committee is going to have more questions than there is time for but that's okay we're just uh let's go ahead and get started on our questions christ uh it's the first hand I see thank you speakers those are those are great talks I have a question for for Anna um you know I've I've the plants that I've worked with I know that some plants are able I'm talking this is about your your comments on incentives I know that some plants um are able to you know be reimbursed or maybe to you can help fund staffing um to to cover the work and then others um are not able to take funding to to contribute to that I was wondering if you could speak to this and if you see this is possibly a hindrance to getting plants to participate um yeah great great question thanks thanks for asking that and you're absolutely right there isn't I don't think anyone incentive that will work in every single jurisdiction um and right I think about Wyoming and Missouri as being able to make stipend payments to the participating utilities but maybe not New York for example so it's going to really depend on what's possible locally I don't think the lack of you know cash incentives will hinder participation among wastewater utilities I think there's plenty of other ways to support their participation and again I'm really speaking to utilities where it is um there's more effort involved in collecting the necessary influence samples because they might not already have an auto sampler setup or they might not already have staff on site so um I think there's a universe out there of incentives that that we can talk about um does that does that answer your question yes thank you yeah Michelle thank you everyone for being with us um I've heard of from a couple speakers already today that there's a strong preference for having the state's public health lab do the testing and particularly given capacity constraints I was hoping that Dr Romero or someone could just uh take me through why that is so important as opposed to building more capacity in the or using existing capacity in the commercial sector yeah I so I'll give you the the view from Arkansas and that is that yeah you know we've we've talked to our governor about this and I was expecting a hard sell and he rapidly embraced this and is willing to fund us as as we go forward to set this up but but he wants to have that data within our system and to have it rapidly available and the concern has been that we're not going to be able to get that data as fast as we want and that's why it's within our system for all of these for all of these issues and and then we can you know if we decide that as I mentioned we could use this for tv for polio for other diseases we can rapidly use them the system that we have over all right chuck yep uh Dr Romero another question for you I the the unsewered population has been on my mind for quite a while and I I'm intrigued by the fact that at least in Arkansas you said there's a strong correlation between unsewered prevalence and your more disadvantaged populations and I wonder if that also correlates with any hot spots for COVID that you've observed and whether or not we know more generally nationally whether there's a greater or lesser prevalence in co of COVID in unsewered populations so to the last to last question no I don't know if there is a greater greater incidence of COVID but we do know that that this area is very rural and so we saw a lot of cases in that area they they you know they they have a lot of the characteristics that have already been described that is yep they're reluctant to for uptake and of the vaccine reluctant for tape for testing sort of feel that they're that they're not at risk because they're in a rural area so we do see a a larger number of cases there and I don't know if Dr Simo wants to make any specific comment about that because he has his finger more on the data Dr Mayor I think you hit the nail right on the head there thank you all right Rekha great presentations everybody and my I have a couple of questions but let me start with Nathan from Utah I have a quick question I really liked your turnaround time it's very impressive three days so I was wondering are you sampling twice a week or just once a week if you are doing twice a week how do you manage those logistic issues in Virginia we are planning to go for twice a week sampling in our phase two but we are working with our public health lab on streamlining how we will be how we will manage handling these samples and still giving that impressive turnaround time like within a couple of days sure and you know I agree logistical issues are really one of the more complicated things that are constant to deal with when we made the switch from our previous academic partner labs to consolidating at our state public health lab back last August that was a huge issue it took months to resolve everything we do sample twice per week and one of the big things was a having a good and reliable courier service that's how we're getting the samples from the facilities to the lab for testing they've been doing great another thing was finding a schedule where all of the facilities could sample on the same days so we're able to basically batch samples in the lab waits until all of the samples come in for a particular sampling set on a given day before they run the analyses and they typically all come in mostly on the same day there's a few from the most remote southwest corner of Utah that requires two courier services and so it comes in earlier the next morning and then the lab does that so there's kind of a day one of those three days is for transport and then it's the next two days are for the lab processes so it's really just finding every little way you can to increase efficiency and to reduce that time and eventually they hopefully add up and then you you're able to get it down but it's not a simple thing whatsoever and it's a constant struggle and finding those days where all the facilities could sample and at least on the same day was quite complicated it was a lot of back and forth with the courier with the lab with the facilities try a different day etc thank you so I have a follow-up question like you just mentioned you are doing twice a week sampling so say are you doing this composite samples if you are doing that then maybe you are using two days to get those samples right like you set up the auto sampler and then for 24 hours and then do you you know freeze that sample and ship those together or like you know just shipping those samples as you get it because we are just designing our strategy so that's what I'm trying to learn sure absolutely most of our facilities do can collect 24-hour composite samples there are essentially three sites that don't just because they don't have the capacity to and they don't want an auto sampler to change it I suspect they're smaller sites I suspect it's very much gets into what Anna was talking about where they have their type of samples that they have to take for the permitting purposes which is what we currently get in theory they could collect composite samples but that would be an entirely new thing and they just don't have the capacity or bandwidth to take that out but most of them are doing 24-hour composites so you're correct that sampling will start 24-hour of previous for example on a Monday morning well end Tuesday morning the courier will come by on Tuesday pick up the sample take it to the lab they're not frozen they're shipped on they're kept refrigerated after collection and then shipped via courier on a in a cooler with ice packs to the lab where they're again stored under refrigerator freeze vine we're reluctant to do that because it can have a negative effect on RNA basically thank you that was helpful I have one more question for you are you using syndromic surveillance and based water surveillance for COVID or some other diseases also as of now just for COVID right now and it's very early days we're still figuring out some of the really basic issues around combining data sets integrating different methods figuring out how best like is one reliable more reliable in certain situations than the other one vice versa we're still figuring a lot of that out but for right now we're definitely still focused on COVID that's all we're testing for currently in wastewater but we very much want to expand in the next year to other pathogen targets where and scenario surveillance will be very useful in that same thing we'll hopefully be able to use a lot of the methods we've developed for COVID to that because of course that data should be collected via and available via syndromic surveillance as well thank you Michelle my question is also for dr lacrosse you mentioned that not everybody sheds virus could you help me understand that and what you think we need to know about the implications of that absolutely with the caveat that folks from CDC are probably going to be more well versed than I so I would defer the knowledge from them as opposed to myself but my understanding is that first off there's a real dearth of basic research around this topic there's been you know maybe a little bit more than a handful of relatively small studies small sample size sample size wise studies relatively early in the pandemic that actually looked at this sort of thing and they found a pretty variable range you know it's I don't remember the percentages off the top my head maybe in the 50 to 60 to 70 percent of people infected with COVID were found to actually be shedding the virus via their GI system so it's not everybody I don't have any knowledge and I'm not sure that anybody's looked but again defer to CDC here on if we know anything about what might affect that like are certain populations or age groups or comorbid conditions or what have you does that certain things factors make somebody more likely to shed or less likely to shed similarly we have essentially no information how different variants affect shedding rate we know have some information on how they might affect viral load and I have in my opinion pretty strong anecdotal evidence that it has a pretty strong effect on shedding which would make perfect biological sense but we just don't have any data on that similarly how does vaccination affect shedding rate we don't really know so there's there's a lot of basic research that would be really helpful to have and it's it's one of those things where despite that lack it's still an incredibly useful system and I think as we get this information and it'll become even more useful Lauren so I'm going to ask Dr to cross a question too so in terms of using I think just for the benefit of us here in terms of using wastewater surveillance viral load talking about increases and and it's you know the the tie together with actual health data which may be waning in terms of testing and things like that seems really really important right because we don't always know if we see something in the wastewater whether it's really going to have an effect in the community in terms of illness and so you know it's really promising that you're bringing a syndromic surveillance data um I I was wondering what the syndromic surveillance like I've also looked into that a little bit what are your thoughts about I mean we've seen relationships with um actually call center testing volumes was an indicator of people looking for where they could get tests that was a precursor um that came really very closely with the wastewater and then and then we saw um not I mean the same data you're using the essence data the um the COVID discharge diagnosis but the proportion out of Ili was a really good indicator did you look at that and also going farther in terms of um hospital hospital data I see bed uses and things like that do you have access to that say I'm talking from the Houston standpoint we have that kind of data which is great for people that have systems as big as ours but what kinds of data do other places have is what I'm curious about like how helpful would that be yeah those are great questions that that's that general topic is something that where is an active discussions within that collaboration I mentioned with CDC and our syndromic surveillance folks is not just how can we make use of things in Utah but how can we build a broader framework that other jurisdictions can make use of as well because that's really the most important thing um and to answer your questions I would have to talk to our syndromic surveillance expert on what data we have in terms of I don't think we've looked at influenza like illness this is you know COVID like illness so there's some pretty broad crossover between the definitions we do have access to some hospital use data I'm not super familiar with it so I would have to investigate the timeliness of it the completeness of it but I think it's pretty good in general so that's certainly a a could be a valuable area to look into as well and that's something we don't want to do like I said this is very early days where we're you know figuring out ways to combine this these types of data but absolutely combining it with other metrics as well like really whatever is available you know one of the classic definitions of syndromic surveillance I learned in grad school was purchases at things like pharmacy so if people are buying more cold medications that might be an indication that something you don't know what exactly what could even just be allergies theoretically but there's something happening there that you might want to pay attention to and being able to link it to things like wastewater data and any other data streams could really help sharpen the picture of what you're seeing so I agree completely but it's early days yet so we don't play yeah so I know that we don't collect that in the syndromic surveillance now in the essence systems we no longer collect pharmacy data so that is a really good point I agree with you multiple data streams would be helpful here I have one more question go ahead actually for our colleague the law professor from Wayne State I'm sorry I'm looking hello I'm here oh hi it's Lance hi sorry um so I just uh the kinds of things that you brought up are really important and we have all dealt with them in health departments and in releasing data and and I wanted to hear a little bit more about your thoughts about the right to know because I understand stigmatism we have cancer clusters in Houston and people that live in the cancer clusters their neighborhoods have you know potentially a stigma and so I know where you're going with that but at the same time there are also communities that didn't know that they had a low vaccination rate or they didn't know that they you know a zip code level and that's that when you know we had we also sample at schools k through 12 schools and we post that information um and the parents want to know if there's COVID in the school so you know where do you see the line of um the idea of a social stigma versus people parents public making their own decisions yeah I mean that's a great question and I don't think it's possible to draw a clear line in all situations I think I think both of those perspectives that you just outlined are are important ones and I think one way to one way to think about this or to to develop policies about this issue is to consult with the community um and so so that that's promoting transparency um ahead of time and saying you know we're developing these systems here's what here's the kinds of information we're collecting here's what our intention is to do with this information and and I think if you can get some community input that might also inform where the appropriate line of the school I I think generally speaking more disclosure is generally going to be a better strategy than less disclosure but but I can see that you know especially the it's the way that the information is framed too if you're if you're if you're releasing information and the the message is that you know this particular community is is a more risky community to live in that could have a lot of negative repercussions but you don't want to withhold that information either and so I think doing this kind of you know having having conversations within people developing systems but also with members of the community to figure out where that where those appropriate lines are is one strategy that I think can be useful I also think that it that it might it might differ somewhat depending on what kind of information you have and it also might it might dictate what at what level of granularity you release the information as well if you're talking about very broad now more granular information might be more useful to people in particular communities to know what's going on in their specific neighborhoods but but there's also a higher risk with that more granular information and so I I I feel like I'm talking around your question in a circle but I think it's because it's a really hard issue to resolve all right thank you Lance um is there any other questions oh go ahead right so I have a follow-up question or kind of similar question Lauren just asked um as a health department partner we were trying to we were in a tough sport like it's so hard to protect the data I mean we are protecting that we have a good governance data governance and we even reached out to each and every utility who are participating with us for their consent before even thinking about releasing our public facing dashboard which it's still like it's still an internal dashboard it's not external um but we have consent from all the utilities and my question is like it's so hard to you know find that balance people are curious like I get lots of email from parents and from you know educated citizens and they they keep asking like soon is never soon where is your data you are analyzing throughout the state and that data is still not out so we need to release data under FOIA act freedom of information act and we don't give the raw data for those reasons like even under that we generally give them a report and a snapshot of the area like people generally ask we are really interested in learning in my community what is the status of that and I'm going for a vacation somewhere so can you tell us how is the COVID trend there so that fine line it's so difficult so I'm just trying to understand when we will have a you know defined framework like what we can do and you know how can we release that data in a more safer way we we don't want you know something like personal genome project pzp like there was an incident happened so we don't like want something like that to happen so being like a little more proactive but still need to be uh you know answerable yeah I mean you've identified some really important issues there and I think that you know the in terms of FOIA and other requirements through these data that's going to differ somewhat state-to-state in terms of how how much detail has to be released and I think a lot of states have been kind of navigating that throughout the pandemic in terms of releasing different kinds of surveillance data I think for the most part the things like the really detailed raw data do not typically have to be released through those FOIA requests although I can't say that definitively in every state I think it's going to it's going to really you know you definitely need to have you know some legal experts in the state look at that as to as to what what could be compelled to be released but but I think it just in terms of making decisions about releasing that data I do think because there is such a high level of public interest in that data when it is released making sure that it's released not just in a in a graph or a table on the on the website but also with some explanation about what you can what what what the what the information really means it can also help I think um not only satisfy people's interests but also to to make sure that that it's not misinterpreted or misapplied or or or or you know you you can frame it in a way that that that hopefully makes it less likely to be um to to lead to to to kind of negative inferences or or any kind of stigmatizing effects thank you all right Stephanie gets the last question hi there so this question is for either Jose or Mike or Nathan um for all that I'm interested in hearing your input on kind of how you've used this data to make public health decisions and if that you know if you have examples that you could share about how wastewater surveillance data has been helpful specifically or if you've had challenges with it what particularly needs to be addressed to better use that data for public health decision making if this is Jose I'm sorry um yes is Mike Mike are you still on yes sir go ahead go ahead and and and answer that question you might you can give them the the data yeah well I think like I mentioned earlier one of the biggest challenges is that we don't really have much to act upon here in this that we have free sites not much of which is coming out of them um you know I think that you know you know those particular sites are extremely borrow areas as well um you know there just hasn't been a whole lot to use in the state thus far which is you know where we're coming from I think I can give a couple examples from Utah um one thing we've been doing a lot less now the state has drastically cut back state um financed or resourced testing individual testing initiatives but beginning back very beginning of 2021 or so we put together it's essentially a composite metric to help rank we use a sort of a Utah specific geography we just call small areas or we divide the state up into 99 different geographic areas based roughly on population size community boundaries that sort of thing and we use that in public health quite a bit so we came up with this composite metric that used wastewater surveillance data in addition to 14-day case rate 78% positivity to kind of build a ranking every week for which of these small areas were most concerning to help direct primarily mobile testing resources into these areas and it seemed to work quite well because we needed some we had we couldn't just send tests everywhere and because there just weren't there wasn't sufficient resources we need some method for prioritizing where we should be sending these limited resources and we wanted to make use of wastewater surveillance data as a independent metric because it's difficult to use solely individual level testing data to send out individual level testing resources you're going to find cases where you're already looking for cases so having this independent data service was very helpful in that regard and we recently made an update to incorporate also syndrome surveillance into a more really more complicated but very similar in idea metric as well and I think it's also been really useful less for public health action I think but just because of the nature of what I'm going to talk about and Amy I remember made this point as well but there have been times where especially the the time I remember well both in that actually now is a great example where we had extraordinarily high case rates at the height of our omicron wave and then everything came way way back down at that same time we had our testing rates individual level testing rates also were coming way way back down in fact at the height of our omicron wave the state had to tell people to unless you're actively sick stop showing up at testing sites because they're just overwhelmed that doesn't do good things for reliability of that data of course thankfully you know things like wastewater data wastewater surveillance data and syndromic surveillance data aren't reliant on individual testing data so we're able to use that to help determine whether okay so we're seeing declining case rates but testing rates are also declining is that just an artifact the fact that we're not testing as many people we're not finding the cases that are actually there and so we're able to use things like wastewater data to help confirm or disconfirm that particular hypothesis based on what we're seeing since it's not reliant on that and I think you know that's right again where the independent data source becomes into play and I think that's just incredibly useful and becomes more so as time goes on. Oh am I sorry did it work? Okay good sorry I just wanted to ask a teeny quick follow up so from like what you're describing is something is very familiar to me too and I just wanted to ask how much so when the signals from wastewater and from other you know data streams are kind of in alignment I feel like wastewater can be very helpful to kind of say yes this is real but have you had any issues with because wastewater is such a new system with when you see a spike in wastewater but not in some of these other systems people don't know how much to trust the wastewater data in part because it's so new and we don't know how to interpret it yet and I wanted to see if you've had that experience or what you've how you've helped dealt with that. Yeah absolutely we have and I would say especially early on so we were one of those early adopter states we just had the right confluence of resources and people in the academic world with expertise who wanted to contribute and the partner agency you want to contribute so we got sampling up and going you know the pilot phase early 2020 and there was I always kind of termed it inertia because I don't think it's resistance per se but there's you know thinking back to when Amy was talking about those time frames like a more usual time scale for implementing one of these systems there's more time to for people to get used to the idea of this as a data source and get used to what it might mean and the strengths and limitations of it as well and take all the into account and that's been you know drastically compressed especially at a time when decisions had to be made now by people who were already utterly overwhelmed and so I think continually proving that it works and then you know here's an example of what we saw ideally in your in your area in your jurisdiction here's an example of when what we are saying now also happened and so this is why we should trust it now and all these other examples so that can be very helpful I think and I've seen a lot less of this as time has gone on and I think there's just been a lessening of that inertia as people become more familiar with it and we've we and in other states and CDC has proven continually that this can be a very very useful data system you know it's not without its flaws just like any data system but it has some real real strengths as well and you know especially now when the alternatives are kind of thin on the ground there's not many other sources of good data right now but ours is still just as good as it always has been and I think people are beginning to recognize that so I think it's a process of time it's a process of continually proving and in working to improve and transparency as well being open about you know this is what I think it means or you know I think this is concerning but we don't we're not really sure of all the specifics yet but it's something that we really need to pay attention to and keep a close eye on all right I want to thank thank each of you for your presentations you're willing this to answer questions we're going to take a break we will reconvene and we will be actually in action at 40 after I would say 35 after but I just don't believe that would happen but we're going to start sharp at at 40 after the hour so so again thank you all all right welcome back everyone after that short break we're going to have several cdc speakers now talk about what the vision of the national wastewater surveillance system is and first I don't know if we're going to hear from Rory or Amy they will it's Rory yeah I got the slide now I just had to look up so I'm Roy Welsh I'm the laboratory lead for a national wastewater surveillance system I'm going to give a brief overview on our future goals and visions of news and if you can't hear me if there's any issues just speak up but I'll assume everything's good I think I have control here yep so I'm starting with just that familiar overview slide for what we have for our national wastewater surveillance system and really this is at its foundation what it was built for PCR type assay data what's missing here is sequence data so you know in response to emerging variants we had to rapidly build in the capacity to incorporate sequencing data into our surveillance program we always thought that pathogen wastewater pathogen genomics would be an important layer to wastewater surveillance but you know the the urge of the pandemic just kind of sped up that process and so I'm going to go over a little bit later in this talk but just on the onset I wanted to give kind of a high level overview of how we're doing this so in our process we're trying to maximize timely data submission we're doing this in a couple different ways our decipher analysis platform at CDC is a cloud-based platform our state and local public health laboratories have well hard-railed data for their clinical SARS-CoV-2 data submissions into our national data repositories at NCBI the sequence read archive the the SRA is in the cloud so we can have cloud to cloud transfer of data a lot of the the requirements for submitting data to NCBI are are similar requirements that we have for submitting wastewater concentration data to our our news wastewater surveillance platform and so oftentimes you'll have a sample come in for wastewater testing and based on whether or not that's positive that will trigger that sample to then go on for for sequencing so you'll have that PCR based information ahead of the sequencing information and so we're developing workflows for our decipher platform where you could give those lists of sample identifiers and all that information that you've already submitted to the news platform will be pre-populated into the submission forms that you have to send in with your sequence data and this is a kind of encouraging positive feedback for timely data submission in addition we're big proponents of open data and sharing and getting data out there and so the the NCBI data repositories are open to the public and they're used for a host of third-party platforms think about the NCBI trace program the NIH funded Rosalind program the outbreak.info and so we want the submitters and the generators of the sequence data to adhere to some some standards so that this data is findable interoperable and useful for a range of different things because the the wastewater concentration data and the sequencing data these are critical public health intelligence and while we implemented our national wastewater surveillance system for COVID it was built to be a multi-pathogen detection platform that was capable of rapidly adapting to changing public health needs and so at the the core of what we do we we want to be a nimble structure that's readily adaptable whether that's bioterrorism threats or emergency response in the wake of some natural disaster or a short-term activation for emerging infections or what we've seen throughout this pandemic is pandemic response and pandemic preparedness so there are three kind of main buckets for our wastewater surveillance strategies there's the core and these are common endemic diseases such as influenza now SARS-CoV-2, RSV, norovirus here we can provide regular consistent updates at a very minimal cost right there's a single sample from that that wastewater treatment plant the next bucket is emergency so here we have a rapid response for an outbreak or a biosecurity threat and here we can provide acute timely information and updates that are all on a flexible platform that can change as the underlying conditions change on the ground the third one is special studies so this is for surveillance of diseases that disproportionately impact a region or demographic and here we can provide such like really specific timely data for diseases of concern so that may or may not be widespread throughout that that particular area recently in association with the the APHL organization they they produced this wastewater guidance document and this provides an overview of SARS-CoV-2 wastewater laboratory setup and the analytical processes that orient public health laboratories as they're they're trying to implement testing and I'm highlighting just table one from this guidance document here because you can see that what we've done with our national wastewater surveillance program is built it based off the existing capacity that we had to rapidly have some data available in the midst of a pandemic everybody's dealt with the supply chain shortages that have impacted everything and so by having this led of 1000 methods bloom approach we've sidestepped a lot of those pain points now we're not totally immune to it and then we've also had tremendous amount of innovation so we have a laundry list of concentration extraction methods that provide robust results for SARS-CoV-2 wastewater testing but this has also led to a lot of issues and as we look to expand beyond SARS-CoV-2 we really need to consolidate on a single test type and primarily that's just so that this data is mutually trusted and understood across our national testing laboratories and so what we're trying to implement is a testing panel that is quantitative it's capable of multiplexing or being massively parallel and it's readily adaptable it's also a difficult sample type wastewater so it needs to be robust inhibitors and capable of really low levels of detection and really the digital PCR platform satisfies all these requirements and luckily for news we already have multiple testing laboratories that are utilizing either the the 296 well digital PCR platforms the the bi-rad or the kaih agent system so we're really going to optimize our news testing panel for these two digital platform systems so this news expanded version one panel will include fecal normalization control a process control antibiotic resistant targets as well as pathogen targets will regularly update or review this this panel with our advisory committee that we're forming to really kind of take a deep look at that what we have on on this panel and whether or not we need to make changes and and what is and isn't working and we'll also develop kind of an emergency assay use panel that can be implemented in certain areas if you have particular outbreaks that could also serve as kind of ground true thing for the the next round of targets to include so for the pathogens we have this table here of potential targets there's an asterisk just to note that this panel composition is not final and it's subject to change the criteria for the selection of these targets where that it has to be shed and stools during infection and it's something that's not commonly shed post infection and chronically ill patients that aren't at risk of ongoing transmission it has to remain stable and enough to detect nucleic acids and there can't be significant technical challenges to molecular detection you'll notice cyclospores on this list that's a really hearty organism that requires some mechanical lysis and so might not easily fold into routine wastewater testing and surveillance and it has to be useful data that kind of complements current existing surveillance so now on this table I have the antimicrobial resistance mechanisms and the genes of interest and the consideration for these ar targets are that they're they're clinically significant resistance and we're going to give priority to emergence emerging high resistant or high consequence genes and really the data has to be actionable right for for public health and not really present in some commensals or environmental bacteria that are going to be present in our wastewater samples and there's trade-offs between large groups or very specific genes that we're still kind of working through on what's kind of optimal but the timeline for this testing is that we'll have an expanded panel that's available for all of our testing laboratories in 2023 right now we're working on finalizing that assay list doing the testing and validations of of these assays and then late fall of 2022 we hope to have the initial piloting testing occurring in some select states as well as these centers of excellence that we're funding through the ELC program last point before I turn to sequencing is in that APHL guidance document there was a link to protocols.io and I really think that this will be important for our surveillance program just to have open resources to the methods the assays that are being used so that if there are you know problems or issues with the assays it's clear you know what the primers and probes are and and what new mutations for circulating variants might be causing potential issues there and that's not just for wet lab but also for our bioinformatic processes so for the remainder of the talk I'm going to switch gears to wastewater sequencing data and variant tracking and just starting off with how we're dealing with our data ingestion plan so we have a umbrella project for organizing all this sequencing data that's part of the news testing system in NCBI we also work with NCBI to ensure that we could have the human read scrub occur for any wastewater sequence data that's submitted as part of news testing this is all just to kind of standardize our wastewater sequencing data as much as possible there's multiple different ways that you could go about kind of pre-filtering the human reads out of your sequence data sets before analyses and we want to try to head that off in a standardized approach that's been validated and entrusted for a host of other projects that are already in NCBI and then we also wanted to provide kind of a step-by-step approach for for how to kind of aggregate this data the metadata the wind where the samples were collected and get that into the NCBI public data repository there are a couple key fields that are in the required submission template documents that are needed to submit any data to the sequence read archive and we can use those key fields like sample ID and the and the decipher platform and then the wastewater surveillance system sample ID in NCBI to link the wastewater concentration data to the sequencing data so that you can overlay these two results in our decipher platform and then we've worked with FDA on our our kind of guidance documents and templates so Ruth Timmy and others in the genome tracker group have built this protocols at IO step-by-step protocol and they utilize the news data dictionary for some of the picklists that are on these submission guidance documents so now we have two federal agencies that are trying to align as much as possible on our wastewater sequencing data and we're utilizing the the phage kind of attributes and standardization processes there so as we shift gears from data ingestion to data analysis we also wanted to provide at least one standardized wastewater sequence analysis approach that all groups could be able to speak apples to apples and and know whatever differences they're seeing from their homebrew analyses they can at least look to this common wastewater analysis pipeline so this is FDA developed wastewater analysis pipeline CWAP it's a bioinformatic pipeline that's capable of ingesting both long read and short read data and giving both mutations QC results and relative abundance of variance through the Freya deconvolution approach this is also included next flow implementation for reproducibility and packaging in addition we've incorporated this into our news wastewater cloud-based analysis platform so this is a scalable cloud computing pipeline that we can scale up if a state decides to dump a backlog of a thousand or more samples and we can quickly run the analysis overnight or we can scale down when there's just a trickle of one or two samples coming in we're not burning resources the analysis pipeline is open source anyone can access it we have standard QC thresholds for general sequencing metrics like Q scores as well as genome breadth and depth that can be filtered so that you can see those results on your your main dashboard and all the the sequencing data can be summarized and linked to the concentration data so we're still iterating over the the final visualizations here but what we're prioritizing is just a relatively simplified news dashboard that will allow jurisdictions to see for their jurisdictions for key wastewater treatment plant of interest what are the overall variant proportions that are present in these samples though also be able to to check key mutations of interest and link up that sequencing data with the wastewater concentration data but if this pandemic has proved anything is we can't be just looking one way so we're building out a a secondary system where you can have detailed wastewater analyses query individual mutations adjust those QC thresholds to look at that key regions of mutations and then also incorporate data beyond just start our news testing partner so international projects FDA's wastewater project and other academic wastewater sequencing data and then all of this you'll be able to download the the raw results the same way that you can download your wastewater concentration data from our news decipher platform so final notice this was mentioned earlier but our jurisdictions that have been funded for wastewater sequence are testing are at all different stages and so to rapidly expand our coverage for wastewater surveillance throughout the U.S. we have a commercial contract that's out it's just recently been awarded the nine month contract to the commercial company Biobot and this is going to provide quantitative testing as well as sequencing testing for 500 utilities that will provide twice weekly testing throughout all 50 states and territories as with what Zach presented earlier the concentration data is all publicly available and data.cdc.gov the COVID data tracker data is also available through COVID data tracker and then the historical data and data.cdc.gov the sequencing data that we have is all going to be publicly available under the news umbrella project and so all of this information can be found and contributed to other public health tools and also research and innovation so I'll stop it there I tried to run through that fairly quickly so we had time for questions and I see there's a bunch coming in the chat okay luckily you guys seem to be answering some of these questions I don't know if someone wants to read them out or how do we address the Q&A session from here I'm going to chime in as soon as I catch up with it was kind of going oh okay Scott go ahead Joe I'll start the cascade there I think Raoul started by mentioning the PMMOV or you mentioned PMMOV and you know these are biological agents in in stool and yeah you can use them for a recovery control a bit but normalizing based on those automatically incorporates their natural variability into your estimate and it's just like the basic indicator concept where our pathogens don't necessarily correlate to our coliform numbers right and so you're building in additional variability so my my gut feeling and is supported by evidence we've seen Seattle at least is that it does not correlate with flow it does not make those changes based on you know Biobot data we've seen they made adjustments initially based on PMMOV but it did not correlate with any change in flow so I just think we really need to hammer on this issue and come up with a good justification if we're going to adjust numbers flow and population seem pretty robust and I know that's not always available but it's something we should definitely talk through I think yeah absolutely and you know we're we're also incorporating additional layers that will help address that like the mobility data so just because you have a population for a given sewer shed doesn't account for like a Super Bowl event or things like that and so in the absence of these other layers these you know fecal normalization controls do provide some additional data and so I put in there that this is version one of our expanded panel and we we will definitely be looking closely at these and whether or not they serve utility to crowd out maybe a useful AR target that that would be more useful for our surveillance program yeah I mean we're talking orders of magnitude variability here yeah and I mean for PMOV just the fact that you need to dilute samples because of the extremely strong signal there also adds another layers of complexity for testing so yeah these are so that raises another issue and I'll end up with this one but the question of innovation we have also seen that depending on the method you're using innovation significantly affects the concentration that you're you're coming up with on your methods and I know digital is better than the standard QPCR but are is there any plan to incorporate specific innovation controls and if so what are they going to do with those are they going to adjust the concentrations on the sample or just rule the sample later now yeah the innovation is you know something that is a real problem for the variability that we're seeing for wastewater testing data and the idea of having your inhibition controls and using that to rule out samples has been something that's had different approaches for different groups some have identified sampling points or treatment plants that are just notoriously bad for inhibition and then they you know do their dilutions before all testing whereas others it's not really an issue for those so I think we're going to have to have some thresholds at least initially while we we work through all these these variabilities that we see so you might set up a manhole testing site in a location it's working well and then carwash opens up just upstream of there and all of a sudden your data is just wrecked so it's really a problem all right I'm going to go to Sandra and then I'm going to come back to Rob or Ami around the human read scrubbing issue so Sandra yeah I great presentation thanks for that Corey I had a lot of questions kind of along the same lines as Scott and rather than get into the specifics although the one I will point out is flow and we have these extra large plants and we actually see that when there's flow we don't see a dilution of the you know a lot of our fecal indicators or the SARS-CoV-2 and we suspect that flow corresponds with scouring so there's a lot of trade-offs on these normalizations and I know when we normalized two different things like PMMOB and again we're in larger systems but so every system is different but between PMMOB some of the bacterial indicators or just normalizing to flow we saw the best correlation when we did nothing so I thought that kind of spoke to you know that there's so many unknowns that and and trade-offs so I guess my question is how will you decide these things you know there's so much um maybe science that still needs to be done to really nail down these dynamics and what we're actually measuring in these trade-offs but that needs to be balanced with needing to make decisions so how are you going to kind of hone in on the targets and I'm especially interested in these normalization factors and how will they kind of be evaluated as you go forward if you should stick with them or maybe go back to the drawing board yeah so that those are all great questions and Sandra and you know my response is I think data builds trust and so by incorporating lots of these human fecal controls in the initial news expanded panel we can get data on multiple different market markers for a wide range of utilities and sampling conditions and so with that initial data we can really drive down into what does and doesn't make sense in terms of a long-term surveillance approach but the idea of just doing nothing gives us no data to actually assess and and work off of so I think it's going to be something that we need to get consistent data for at least a defined period of time and have you know quarterly reviews to see what is and isn't actually improving that correlation between the wastewater concentration data and you know the overall syndromic surveillance data that we have maybe there's certain areas that have really high levels of clinical testing or other information that we can kind of use that as a gold standard to kind of compare the two together great yeah thanks for that Rob Hey Rory great presentation I just had a question about the human re-filtering which is which is a really hard problem and we were just in the position of having to reprocess terabytes of data with the new human genome build which includes a better Y chromosome from long-read sequencing and that picks up a whole lot of sequences that were missed previously but but I was wondering for this application there's a lot of concern especially about minority populations and potential reuse of the data what what procedure are you thinking about to take into account the indel's that are specific to different populations that may not be adequately represented in the in the current human genome reference databases and will that be an important consideration for depositing the data in a way that's reusable but at the same time protects those populations from having their human reads deposited yeah so we don't want to be throwing away informative data that could actually help for for the targets that we have but we also don't want to to accidentally release any you know human data that that might be incorporated there so our current approach was to standardize on the ntbi human re-discoverer that they have and you bring up a good point where you know none of these tools are perfect and so maybe it's worth pilot projects that can find ways that we can flag and remove some of these indel's and other sequences that might pass through the initial filtering approach but it's it's it's certainly a problem where there's no real great answer here it's either we wall off this data and we don't allow it for for public use or we take a really hard line stringent approach and we throw away a lot of useful data but letting all the different jurisdictions come up with their own approach also breeds a lot of inconsistency in terms of a uniform surveillance approach so yeah thank you for that question that's a good point there's intermediate approaches like db gap where it's public publicly accessible but gated although if you can if you can find a way to keep it out of db gap while the same time while at the same time maintaining privacy that greatly lowers the barrier to reuse and would certainly be highly desirable if it can be done that way that's a good point yeah you're right so i had a more kind of big picture question that say if you have a limited part of money you could do two things with it you could either just expand the current surveillance system to you know include more sites more frequent testing etc or you could invest more in research to figure out like what is actually the value of data we are getting from the existing system is it you know is it valuable and leading kind of public health action or you know trying to figure out if there was a bioterrorism attack would the current system actually work or we just think it'll work but we really don't have credible evidence that it could work so i'm just curious like which one of those parts would you invest more in yeah i mean there's trade-offs with both so if you go with the this kind of refined detailed approach where you can really hone in on a couple specific questions around the risk of you know they're not being a prevalence of the target that you're after and and then you walk away with not a whole lot of data and then if you don't expand to a broad national scale especially at times like this where our clinical surveillance is that those denominators are getting a lot less useful and that data is becoming more sparse you you've risked areas of the US population going dark and we could have spreading wildfires that we have no view on whether or not we have increases and SARS-CoV-2 and the like um and so i mean our approach was to get some baseline expansion of wastewater testing on a national scale but we have funded specific projects that do look at particular scenarios like what you're you're suggesting here so we have one mechanism which is the the broad agency awards and we funded a a study at a university system actually here in here in georgia the university of georgia has detailed patient clinical information as well as detailed testing on their campus population and wastewater surveillance at the facility dorm level as well as you know from the the public health system. Rob Knight also has a group with the UC system where they've done the same thing there and so those are two examples of having uh really high level trusted clinical data that they can pair with wastewater data to really see what's the the maximum kind of endpoint for for this surveillance approach and so i think we're we're trying to do both at the same time here and as we look to expand beyond SARS-CoV-2 i think we'll try to get a broad coverage so that we can get data across you know a large geographic population here in the US but we'll still need these kind of detailed study approaches in order to see what what the limits are. Thank you. Scott we have time for your if you want to ask those questions is our last question the ones you put in the chat we could do that. Sure although i can't open chat and mute at the same time apparently. So i had two general questions first one well one general and one specific one maybe since we're talking about sequences do the the specific one first when you're looking at the the variant tracking question are you seeing every sample is going to be sequenced from here on out or are you looking at to use that sequence data to generate specific primer sets that we can quantify and target directly um individual variants. Yeah so um what many groups did at the onset of sequencing wastewater was to take the same clinical tiled amplicon approach and then apply it to wastewater but then with each new variant that comes out there the really hammering on that primer set and so you get areas of the genome that just go dark and you have to incorporate new primers and so any kind of primer targeted approach is going to run that risk but i think that in terms of return on investment for not just sequencing background and noise and actually doing a targeted sequencing approach there's going to have to be some type of rapid kind of tiled targeting sequencing approach until that sequencing costs or capabilities improve and so the that's been uh shown to be kind of a successful strategy it does have its drawbacks but when you're talking about ar pathogens or um like the emerging multi-drug resistant use uh candidates you can do target at regions of the genome and get information about um you know what clade is circulating and it goes beyond just presence absence uh but to what subtype is there. Okay so following on that the sequencing then if we're using sequencing moving forward what is that going to do to your timeline i know you want to make it as timely as possible and that's the focus but you know simply in in analysis the sequence data is is not quick um exactly and even generation of that that sequencing data so a lot of these workflows you wouldn't trigger a sample to be sequenced unless you had a concentration that was above a certain threshold because your likelihood of getting useful data was just not there um and so that timeline issue I think is going to be a little bit extended the same way that we have for clinical testing where you get your PCR positive negative and then it go gets forwarded on to sequencing we have the nine months contract that I referenced earlier we have a requirement from when the samples arrive to when that data is publicly available of 10 days so it's not you know weeks you're not a historian of you know an outbreak you're still getting somewhat timely data but it's not going to be as rapid as your your digital PCR now some of are really well funded laboratories uh like again Rob I'm thinking on you but do your previous publications have pretty remarkable turnarounds for wastewater sequencing data I don't know that our standard public health laboratories are going to be able to replicate that in the near future but that's our goal to kind of optimize the efficiency and turn around time for everything from our concentration-based testing to our sequencing testing so my second question was very general and this this may predate your time at CDC but I'm curious to what extent with with the fallout from BioWatch and the false positives as we were doing kind of the you know biodefense surveillance um that rollout to the the state health labs was not um well it had issues a lot at reagents going stale and other things so how have the lessons learned from that been incorporated in the rollout of news to the state labs yeah I mean that was a national program that was instituted by the department of defense uh whereas this is directly public health and public health run so the funding mechanism that we use is the the ELC funding that uh state public health systems can budget and then uh you know kind of run their own um organization for uh how they're going to actually land on the deliverables of testing we're also working with companies so right now there are two digital PCR platforms that support 96 well uh plate formats that's the kaijin and bioret and so we're working with these companies to just say you know we're hearing concerns about supply chain and not just for kits reagents and instruments but also technicians getting out in timely fashion so working with them to have build in additional safety reserves and also uh what what they have in terms of uh you know staff to to really make sure that we don't have areas going dark for our wastewater surveillance because of of things like the they can't get a technician out there for the instrument um so uh these are you know these are problems that are forefront in our mind especially with the supply chain issues that everyone's felt during this pandemic thanks all right thanks thanks very much and thank you Roy for for excellent presentation and being willing to answer all those questions um our final speaker today is Vince Hill um who um basically um directs the the Waterborne Disease Prevention Branch at CDC and he's going to discuss the motivation and value um hopefully of uh this national academy study yeah thanks very much um yeah it's really a pleasure to be here i mean wow that last just basically that last uh presentation all the conversation in the chat around there it's just it's just thrilling uh frankly i mean for myself i want to go back to the laboratory my trainings and environmental uh microbiology and uh engineering so uh just super exciting to have so much expertise and experience you know focused on this on this on this matter uh so really excited for the kickoff of the of this process we're going to do this uh i'm going to rely on uh folks from nascent the advance my slide so next slide please i think there we go thank you um so you know over the course of today um you've heard about the design implementation of news as well as some of the challenges imposed by rapidly standing up a new surveillance system within the context of an unprecedented pandemic response um you know it's just been incredible to see in the last 19 months or so uh academic researchers utilities state and local health departments private companies and multiple federal federal agencies you know have built infrastructure to do so many things it's been incredible so including to collect wastewater samples uh from communities of all sizes across the country um and measure the concentration of SARS-CoV-2 RNA and wastewater samples despite the differences in lab capacity supply change challenge supply change challenges that we had early especially early in the pandemic and the changing biology of the virus uh infrastructure has been built to transmit the test data and all of the necessary sample metadata to state and federal databases infrastructure to analyze the data and to report the results to health departments and communities in near real time generally within five to seven days after sample collection so and then state and local public health agencies you know are using this data to inform response decisions particularly resource allocation and we've seen just an incredible increase in interest from uh from the public so for example the wastewater surveillance page on a COVID data tracker is the most visited page after the data tracker landing page and the public so the public is clearly interested in better understanding the status of COVID in their communities and it's it's really exciting to consider that they may be using this data to inform their day-to-day choices and understanding what's going on in their community so it's really exciting next slide thank you so despite these successes there are still areas of development for news to build better science around wastewater surveillance and to build a more sustainable surveillance system so thinking about some of these areas it's clear that better metrics are needed especially measures that are scientifically valid but also readily interpretable for non-experts and as we move to a multi-pathogen system we will need to reevaluate the appropriate sampling frames for wastewater surveillance so things like you know which locations should be prioritized what is the appropriate sampling frequency the answer to these questions will likely be different for each target so you know is there a reasonable single sampling frame or do we need to accommodate different approaches for different targets for a testing-based system such as news there is always space for improved methods and so while we want to make the assays more sensitive and more specific we also want to streamline the workflow to minimize handling reduce opportunities errors increase throughput and standardized data outputs and you know we saw in the context of the COVID response we still need to understand the impact of vaccination and variants on people shedding has a big impact on the data and another important context for this is the data modernization initiative that CDC has undertaken to improve data flow data sharing and data compatibility across the agency's many data systems we have been including data modernization principles in news data systems from the start but there are more improvements to be made especially around automated data transfers and finally wastewater surveillance like other environmental microbiology activities exist outside the ethical frameworks for clinical testing but the impacts of many of the same print but but the the surveillance impacts many of the same principles so things like consent privacy and stigma are are really important to consider for wastewater surveillance like they're well well thought of and considered through clinical testing we really need to have those in place and thought of around wastewater surveillance we must be transparent with communities about you know what data are collected what information is not collected and who is making decisions about these samples next so as news develops we want to ensure that we are following the best science any organization has potential blind spots and can develop tunnel vision in its initiatives which create challenges to identify looming problems and novel opportunities as we drive towards you know it's our goals so developing news so rapidly and under such extreme circumstances presented by the pandemic required prioritizing efficiency so we want to ensure that we aren't sacrificing rigor in this process wastewater surveillance requires expertise from a broad group of stakeholders including wastewater engineers environmental and clinical microbiologists epidemiologists and health communicators so there's no better way to access the best of this varied expertise than through the national academies of sciences engineering medicine so super excited for this to get started so really the time is now this is perfect to be doing this right now the science has grown rapidly for example since 2020 over 1100 articles have been published on wastewater surveillance you know and we have the opportunity to direct new research where it is most needed so the information from this process is going to be really influential for that and this is the time to leverage leverage this moment of great support and investment in public health to build sustainable systems to prepare us for the future next slide please so as this expert panel process begins I'd like to revisit the statement of task for the panel and thanks to the guy Palmer for reviewing this a bit earlier so the nasim expert review is divided into two phases the first part of phase one is a landscape analysis which includes answering some pretty fundamental questions like you know what is wastewater surveillance characterizing that but how is it different from existing surveillance and wastewater monitoring systems how has wastewater surveillance been used within the COVID response and you know what is work and what hasn't next slide so the second part of phase one is an evaluation of implementation strategies and approaches here we want the panel to expand its review beyond COVID-19 and consider applications for other infectious diseases we really look forward to hearing the panel's views on opportunities to contribute to the control and prevention of disease more broadly and where there may be hurdles to expand the views one thing to note in the interest of keeping the scope of the review manageable is that we are not including non-infectious agents in this panel review but next we are asking that the panel consider the characteristics of a robust national surveillance system things like you know how should it be structured what are the roles for each implementing partner how should it be coordinated what guardrails need to be in place to ensure that the data will be used only in support of the public good to keep the scope of the review within reason we encourage you to focus on community level surveillance rather than applications at the building level and to focus on implementation in the United States rather than broader global implementations or you know in low resource settings and finally for this phase we'd like to hear from the panel and ways we can increase the public health impact of wastewater surveillance next slide please so then in phase two you will have the opportunity to really dig into the technical details we've heard a lot of technical details so far just just today so this is going to be really exciting to hear what you your discussions and what you put forward in this area so you know but addressing issues like what are the strengths and limitations of different sampling designs laboratory methods and analytic approaches are there other data sources that can be combined with wastewater data to provide stronger analysis and as in phase one in phase two here the focus is going to be on infectious diseases finally the panel should describe the research and development needs as well as the resources needed to support wastewater surveillance so actually that's informational slide but you know just a couple thoughts in closing you know over the past two years it has been so impressive to watch an entire field turn its focus to wastewater surveillance so many have volunteered their time and the resources to build wastewater surveillance capacity news would not exist without them and we want to thank the panel again for giving your time and expertise in this effort news and public health will benefit greatly from from your input and your efforts through this so really appreciate your time thank you so much thank you vince i'm sure there's going to be questions but i'm going to take prerogative and jump in uh first um but because one of the questions that has kind of come up and it was actually it's something i've been thinking about for a while but in the presentation from utah they had 40 some sites they tested and kind of my question is do they need did they really need 40 or do they need fewer that are representative and that's where you concentrate your resources or do they need more to get coverage and it kind of comes down to something that michelle and i were talking about is what's the definition of community because that you know i feel like it's a legal thing you're trying to decide what the definition of is is which if you have a long memory you could might might remember when that came up but when cdc looks at community um what are your thoughts on that yeah and i know i'm just from my perspective i know the team has really thought through this a lot and and certainly within the the context of these you know national commercial testing contracts etc um and using criteria you know health equity based criteria so you know making sure we keep in mind that we're not just focusing on the large population centers the urban centers etc right because um i i don't know that we get a good sense of what's what's going on in communities again that word though what's a community across the country so rural tribal etc so um those just might you're right it's it is a big issue and clearly needs to be thought of especially as we go beyond coven and we start talking about this as routine surveillance you know for other diseases etc because that really does that could change um some of the um the the aspects of it that you want to build into the system let me just hold off there and maybe just ask you know amy or anybody else who's really looked at that issue of how to define community surveillance if you want to add any thoughts i mean i will just add that yes this is something we've been thinking about quite a bit um particularly with what is the appropriate coverage that we need to accomplish i think it's unreasonable to think that we'll get to a hundred percent of the utilities that are you know true community serving utilities not necessarily the lagoon style that um and i was pointing out um and i don't think that is necessary to get the kind of public health data that we need um but is it you know some percent coverage that we want to be able to capture is it particularly prioritizing vulnerable communities um or even is it a dynamic sampling frame and so core surveillance has one level of coverage and frequency and then if you want to do for example response um emergency response surveillance that changes frequency and coverage that's another um possibility and there's advantages and disadvantages to both approaches as far as what constitutes a community we've done that thinking as well i don't know if zach wants to chime in on this v and i were going through this a while ago because we got exactly this question how many communities are covered by wastewater surveillance and if you really want to highlight sort of the extreme of that um lauren is actually a great example in houston they have 39 sampling sites to cover one city is that 39 communities is it one community is it something in between it's not an easy measure which is why we've sort of directed towards sites as opposed to communities but i think it's something we're going to have to um put some definitions on as we go forward specifically sure do you have a follow-up go ahead yeah go ahead michelle yeah so uh i appreciate what you're saying about um not being fully resolved amongst yourselves about how much scale we're taking this to to say that we're community-wide but i was actually sort of thinking about where you landed at the sort of the more granular and what is the smallest unit of sampling and testing that you would consider to be a community because i think that's the most salient for thinking through the ethical issues so again zach may have better numbers on this than i do but i think our smallest facilities have in the range of three thousand uh people served by that facility uh wastewater treatment plant um that's about as small as you're going to get and have a serviceable plant that has the capacity to participate in wastewater surveillance but we have had discussions about other types of community settings for example um a large subdivision that has a shared septic tank if you sample upstream of the septic tank it has a lot of the same um capacity and characteristics of a wastewater treatment plant it's just being handled differently once it gets to the treatment part and so there may be a justification for looking at that as well i know washington state is really interested in those kinds of applications and so i think those are all considerations i will say it does link back to the ethics issue so we do not release data publicly if the population that's captured is less than three thousand people because at that point you have an increased risk of being able to identify who the case is that's contributing to that sample and so we just that is the the boundary that we have on public data release but certainly for internal use we don't have we will look at samples from as small communities as it is feasible to look at sorry one more follow-up question on that um in the statement of task in the paragraph below the bullets it says um community wastewater-based disease surveillance implies sampling at wastewater treatment plants and does not include local surveillance and neighborhoods or institutional scales i i know early on we talk about institutions but i wonder if your thinking has evolved since then so that you're more open to the neighborhood or you really want the committee to think about wastewater treatment plant sampling and then a different scales of those wastewater treatment plants so i think our our thinking has evolved a bit um but it's really about the larger plants um for that question so some of our very large systems like l.a county is a great example they serve i believe five million people all total and you're not going to get a very sensitive assay if you're testing just at the wastewater treatment plant so there it makes sense to sample within the collection system so that you sort of break that big five million person population up into smaller um maybe only one million person groups so their sub sewer shed sampling would be appropriate what we sometimes hear people talking about is essentially tracking the sample and the signal through the wastewater treatment system up to wherever the source is that is not um a use of wastewater surveillance data that we want to support right now and so that kind of sub sewer shed sampling where you're trying to isolate hot spot communities and things like that um we think that's really beyond um what news wants to pursue and so i would not consider that part of the scope of work but if it's about improving the sensitivity of the surveillance approach in these very large systems i think that is within the scope here does that clarify for you stefanie yeah and the group all right scott yeah so i have two questions so there was a comment that's made about variability in terms of one of the challenges you're facing um in some modeling that we've done one of the biggest sources of variability is still the shedding and most of our shedding data thus far is like uh was mentioned earlier is from the beginning of the pandemic on a very different variant than is currently circulating is there any um efforts that you're aware of or that you're supporting that are going to characterize shedding patterns for different variants and how this might impact how we do data interpretation yes um totally agree with uh Nathan's comment earlier that we don't have enough data on this scott your comment now that we're missing it we are pursuing that data as much as we can so we know there's a few NIH funded clinical trials that have a sort of side study where they're collecting uh stool samples and doing quantitative testing there so there's limited data that will be coming out of those we are also going to be funding a study to get additional data uh on fecal shedding over time so longitudinal data of all types of severities um and hopefully we'll be able to get enough participants to be able to look at vaccination status and variants um of course the ability to do any of those analyses will depend on the state of the pandemic what variants are circulating people's willingness to participate so we'll have to see what ultimately the participant group is in this study but we are hopeful that we will be able to get more data in um and looking at you know hopefully in the range of 50 to 90 participants as opposed to the early studies which were you know eight that's excellent that's great to hear i one other question regarding the use cases so the other piece as far as the expansion of the panel beyond SARS the use cases for different targets may be considerably different and does that have any impact on the design of the approach that news is going to use yeah i think that's what we're wrestling with here um because certainly um i think the easiest place to think about that is sampling frequency for covid the more frequently you can sample the better off you are and the more useful your data is so twice a week is really the minimum to get really useful data for action if you're testing something like antibiotic resistance twice a week you're wasting a lot of your effort and time um that is not a useful sampling frequency so how do we um come to a sampling frame and testing workflow that is most efficient while also protecting all of the public health action that we want to get out of this data and that's something that we're going to be thinking about in great depth this year as we move towards that multi-pathogen system and really it's a trade-off between efficiency right spending money where it is most useful um and time uh you know personnel resources as well but also being mindful that any kind of dynamic testing system where you're changing sampling frequency testing type all of that it has a um for lack of a better way to put it a mental burden right and you introduce more more um potential points for error um as things get more complex so we're trying to figure out where the sweet spot is for that um and you know would love to hear the the committee's thoughts on that yeah I I'm going to jump down to Chuck here in a second but I I'd just also point out that in just looking at different pathogens it would not only be temporal but obviously spatial if you're looking for drug-resistant C. oris I would not look in rural Montana um I would there are certain places I would definitely um put that and I'm sure that's a consideration Chuck I'm going to jump down to you because you were you were responding something earlier and then yeah I mean Amy I think your your response on the community question to my mind sort of muddies things up I mean I I understand sampling in a treatment plan which I take to be the head works the treatment plan typically um but the moment you know you throw in LA as as your exemplar of wanting to go upstream I you know I think the issue is not population size it's heterogeneity and um you know I think it's easier to tackle the question at the head works of the plant the moment you want to start to look at heterogeneity um in whatever scale population you have a heterogeneous population in you get into the question of you know where is the heterogeneity how much is the heterogeneity and to what degree is the variability temporal versus spatial which opens up you know a lot more uh site specific questions to consider so you know I think the charge as as written with my understanding to be the head works as well understood I I hate to see without a lot more detailed deliberation expansion into the collection system yeah I I mean that wasn't really a question it was more of a comment but I will respond I think you are correct there and certainly being able to go out into the sewer system the collection system and do samples and understand what they tell you really requires a very good and accurate hydraulic map so you know what is actually flowing through those pipes and how much and a lot of our systems don't have that unfortunately um and so you're right in those cases it does just introduce more variability and the other piece to keep in mind um as we think about subdividing systems is that we are not in a lockdown anymore which is where we were when we first started doing wastewater surveillance and you really only worried about where people lived now we have to worry about people moving between the different sampling zones and so the smaller your sampling areas become the more of that sort of transient you know people going from home to work to school all those places will impact the numbers that you see and your sort of consistency over time so Chuck I totally agree and take that take that in the spirit with which it was offered and I think that's something that we really need to think about again really only see this as an issue in those very largest systems where you know the flow through the plant is just so massive that we might lose some sensitivity okay we've got about four questions we have 11 minutes because we have a public comment that we need to respect that individual's time so quick questions and brilliant short answers would be would be awesome Reca all right I'll be super quick so I'm kind of developing on Amy's answer about you know and your question to like how to figure out how many sites are important and where those sites should be so as an example from you know jurisdiction I would like to share our experience how we designed real quick like in three sentences so we had a criteria like we advertised our program on various platforms and reached out to utilities as much as possible and then first primary criteria was just to enroll utilities who were having capability to sample and they had interest in sampling and second thing was like we really wanted equitable representation from the state so we didn't want all the sites clustered in one part of the state like our Hampton Road Sanitation District partners were pioneers in this wastewater surveillance and we had their data from starting they were sharing every all the samples data and samples so we could have enrolled them and just you know make our total number to 25 we thought like let's go for 25 and there was hesitancy initially like having all the you know sites which we were really interested in enrolling especially from Central Virginia we don't have many sites we have just one site and I really need to convince them to come on board and other than that we have lots of sites from Northern Virginia so Southwest Virginia is more low healthcare setting sites so we really needed to go out and about there to enroll some sites from there and now we are in our phase two we are planning to enroll more sites from there so sort of you know it's difficult to figure out like how much is enough but maybe something like that can help thank you all right thank you and I mean I think you're next great thanks so much I wanted to follow up on John's point about trying to understand the dynamics of shedding for any disease and especially in the case of COVID-19 evolving variants our group recently published a manuscript that describes the shedding dynamics in feces of the original SARS-CoV-2 variant of about a hundred or so individuals over the course of many many months but the amount of work that went into actually collecting those samples and analyzing those data was quite substantial I would love to see similar types of data for example in the context of Omicron and BA2 but the question is really whose responsibility is that and in this report is is this topic of you know the the complementary data that we would need from individuals part of what you'd like to like us to comment on it's definitely within the scope of the report so it shouldn't be a focus but where there are big data gaps that are needed to really push forward the science of wastewater surveillance I think those need to be flagged and clearly the more data we can get on fecal shedding and the impact of variants and this is going to be needed for all of those other pathogens too highlighting that will be important Marissa so I had a quick question about sort of your thinking around so you mentioned you know as part of the scope of the charge sort of thinking about what other pathogens you know the system could be used for and I wanted to hear a little bit more about about sort of which pathogen like what I saw you know in the in the three buckets and that kind of thing how do you feel that emerging pathogens fit into this and and sort of where do you think that sits so personally I'm really excited about the application of wastewater surveillance for emerging pathogens because that's really where we see this impact of the skew and clinical surveillance the strongest because we first become aware of them in the most severe cases in the hospital and very often it's years before we really understand community levels and so wastewater surveillance gives us a low barrier to entry way to ask that community level question and so I think that it has a lot of potential for that and would really like to see you know that concept sort of really explored and fleshed out and hear the the committee's thinking on that and sort of what would be the criteria of an emerging infection that you would want to see before you think that it is a good target for wastewater surveillance. Hi Amy I have a question I think at some point you talked about how you first see this transitioning to primarily public health labs and with a specific method you know right now it's a big mix of academic private public health lots of methods you know how academics we love our methods and we don't want to give them up right so I'm wondering as we think about this report are we envisioning this future you kind of you said where it is at the public health labs it is a very specific method or is there space to kind of think about a hybrid system in between not necessarily what we have now but that still has these other these other types of labs and these other types of methods kind of working where can we explore that space. There's definitely room for exploring that hybrid space I think right now there's not much question that we are too dependent on academic partners they we are hearing that from the academics that they want to be able to free up their staff to do research and not be bound to this turnaround time however we have also heard from some of our state partners that they have great relationships with their academic partners they don't want to change what they're doing this relationship is working for them right now and so we need to figure out how we're going to address that is it a transition period where it's just going to be a longer time before we get everyone to public health labs or is there some stable relationship and sort of ratio between these academic public health lab partnerships and the ones that are straight public health lab implementations so I think that is definitely fertile ground for exploration. All right are there any other questions? Yeah okay I have a quick one and I'm sorry to jump in at the end of the line but I just want to yeah I just want to Amy you mentioned data gaps how much should we maybe comment on or explore what research needs to be done which is a little different than data or method validation you know I see that as maybe two separate things and I know we've talked about how you know research covers that spectrum but can you maybe just talk a little bit about delineating those two things and maybe how we might handle that in the report? Yeah so my thoughts on that is I would really encourage you to focus on the research gaps that are critical for moving forward the application of wastewater surveillance so there's lots of ways that you can look into how wastewater surveillance can support other research needs and there's definitely room for that in the future but for this report we really want to focus on the application for public health and so what are the gaps that we need to address that right now specifically for those infectious targets and how will that inform the way we are implementing and coordinating the system is that helpful that might have been a little too spot on and snacky that could probably use more description yeah no I think the app I think that you know the application kind of bin is a good way to put it okay anything you need for application yeah all right and our last question Michelle could you clarify whether you see the phase two report as including any of the ethical legal or social issues that we've been talking about today or really focusing and that focusing on but expanding on the technical issues? I think it has to particularly because that's where you will start thinking about things like future pandemic potential right so detecting that unknown pathogen that we don't know about yet and being able to have the system that we all want to detect the next pandemic and whenever we start talking about that ethics have to go along with that and so I think it's going to have to be in the phase two report all right thank you we do have one public comment Brian Swalla I just like to call on you Brian hello can you hear me yes excellent well thank you for the opportunity to provide a comment today just a tiny bit of background and then I'll make our summarize my comment I'm a microbiologist and molecular biologist with IDEX laboratories in Westbrook, Maine I've been involved with SARS-CoV-2 testing from the beginning of the pandemic when IDEX rapidly developed and validated two products and testing protocols for detection of SARS-CoV-2 and wastewater I and my colleagues here at IDEX have had the opportunity to collaborate with a broad variety of organizations and many individuals to share information and assist with the implementation of testing methods we've submitted a detailed written comment I'd like to just offer the key points here to avoid to achieve the robust and integrated wastewater based infectious disease surveillance program three foundational elements to consider could include agreement on what type of data should be collected the quality of the data the objectives for that quality and lastly how and to who the resulting information will be communicated and acted upon but as we've heard today that the scientific community community is keenly aware that health related actions must be based on reliable and high quality analytical test data testing methods for any type of infectious disease surveillance must be performed by laboratories with demonstrated competency which is routinely accomplished for other federal programs through a laboratory accreditation process typically data quality objectives should be established prior to program implementation however this was not necessarily an option during the SARS-CoV-2 pandemic many different testing methods for SARS-CoV-2 were developed as we've heard by a wide variety of organizations universities public research organizations private laboratories and industry all converged and collaborated in developing test methods and indeed it was one of the most collaborative scientific endeavors in many of our lifetimes now that we as a public health community are set to move towards long-term monitoring it is critical that data quality objectives and data uses are identified and clearly communicated as a manufacturer we make myriad design choices when creating analytical tests and having a clear understanding of data use and data quality objectives is imperative to ensure that those decisions are made well and with the best interest of public health in mind thank you and happy to enter any any questions if that's okay super thank you brian for those comments are there any questions to brian i think that was quite clear and congruent with a lot of what we've heard today brian so so thank you and thank you for that perspective if there are no other questions i want to thank all of our speakers and brian i include you in there i want to thank you as well and to everyone else who's joined the meeting today information on future meetings will be posted on the study website and you can also sign up on the committee website to be added to the mailing list so thank you and enjoy what's left of your day depending on your time zone so take care