Wastewater Surveillance for Public Health

[00:00:00] Max Herzog: Welcome everyone to this month's edition of Water Data Forum. I'm Max Herzog, a program manager with Cleveland Water Alliance. It's my great pleasure to welcome you on behalf of the presenting collaborators of this series, Cleveland Water Alliance, the Water Environment Federation, and the Midwest Big Data Innovation Hub.

[00:00:34] We've been convening this series for a couple of years now, really diving into a variety of topics around the themes of water and data, and really excited to dive into this month's edition with you today. Today we'll be speaking about wastewater surveillance for public health, a really poignant, exciting, and emerging topic, in the field of water data, and, we're really excited to have you here to be part of the conversation.

[00:01:02] Throughout the panel discussion here today, we really encourage you to submit your questions via the Q&A button in your toolbar at the bottom of the screen. You'll see it right next to the chat, but easily confusable with the chat. Please do submit those questions via Q&A some panelists may be able to actually type in some responses on the fly.

[00:01:26] Otherwise, we'll be looking to that Q&A list first, when we get to the open discussion section of the session at the end here today, so please do feel free to chime in with those questions as they come up and we'll be, we'll be turning to them primarily at the end of the session today. As I said, I'm Max Herzog, program manager with Cleveland Water Alliance.

[00:01:51] It's my great pleasure to be your facilitator for today's session. We really have an all star set of panelists today in this field of wastewater surveillance. So, I hope you'll join me virtually, in welcoming Dr. Amy Kirby, National Wastewater Surveillance System lead with the Centers for Disease Control and Prevention.

[00:02:14] Dr. Anna Motra, Wastewater Surveillance Program Director with the Water Environment Federation. Raul Gonzalez, Environmental Scientist with Hampton Road Sanitation District. And Nathan LaCrosse, Wastewater Surveillance Program Manager with Utah Department of Health and Human Services. So, we're really excited to have our panelists here today.

[00:02:37] And we will go ahead, and dive right into our discussion. So, by way of sort of introducing this topic, I'm wondering if we can start with the question, what is wastewater surveillance and why do we do it here in the US? And I think 1st, I'd like to turn to Amy to sort of kick things off for us here.

[00:03:02] Amy Kirby: Sure. Thanks, Max. And thanks for inviting me to participate in this. It's always good to spend a Friday talking about wastewater surveillance with, Water sector folks, some of my favorite people. So the idea of wastewater surveillance is actually pretty simple. So, instead of testing individual stool samples from individual people to understand the prevalence of a disease, we're going to use wastewater as essentially a pooled community stool sample.

[00:03:33] We know it's a lot more than that. There's also urine in there. So if a urine test is feasible, that may be an option as well. Now seen with impacts, skin shedding, showers is also going to contribute, so we're realizing now that a lot of other clinical samples also get pooled and wastewater.

[00:03:54] But the idea is that we're going to look for those pathogens, measure their concentration, and use changes in the concentration of those pathogens as a measure of changes in cases in that community. So our cases going up, are they going down? And how fast are they changing? This is not a new idea. Polio surveillance has been using wastewater testing.

[00:04:19] Since the 1960s, but they have, they use a little bit differently because they are looking for an infection that is so rare. They use wastewater surveillance is just a plus minus. Are there cases in this community or not? And if the answer is yes, then they go in with vaccines and offer vaccination to that community with something that's as prevalent as COVID.

[00:04:43] We have to have a quantitative result. So, plus minus. Unfortunately, almost every community in the U. S. right now is plus so that is not enough information for us. And so we have to go to quantitative measures to really look at trends and one of the things, as we think about expanding beyond COVID that I always want to emphasize is that we are doing this for public health surveillance.

[00:05:08] And so there needs to be an action that's linked to this. So, this is not just data for data sake to understand what's going on in the community. But when we see increases, what are we going to do? How are we going to act on it? And early in the COVID response jurisdictions were doing things like citing mobile testing units and communities where they saw increases or mobile vaccination units.

[00:05:32] Now we see them using it a little bit differently they're using it to message out to communities that cases are going up and to take precautions like wearing a mask or not participating in large events. They are also using it to identify communities that may need additional clinical resources.

[00:05:51] So we know when we see an increase in SARS-CoV-2 and wastewater. Within a week or 2, there's going to be an increase in cases reporting to hospitals. And so we want to make sure the hospitals in those communities are ready for those cases coming. And so that's really what we've been using this for. And as we expand to other targets, we want to keep that in mind.

[00:06:12] There are a lot of things we can measure in wastewater as we started thinking about other applications of this platform, which we really want to expand to. There are a lot of things we can detect that don't have an action attached to it. So being very clear that there is something that can be done to protect the community once we get these detections.

[00:06:36] Max Herzog: Thanks so much, Amy, really comprehensive kind of bird's eye overview of the history and the landscape as it looks now. I'm wondering, Nathan, if you could speak to this, you know, coming from Utah, what this work is looking like at the state level and sort of the value proposition and the impact that you're seeing there.

[00:06:55] Nathan LaCross: Absolutely. Happy to. Thank you for having me, you know, first off, obviously, I have to say, unsurprisingly, everything that Amy just said applies not just at the very broad national level, but at the state level as well. In a lot of ways, it's sort of a microcosm. Each jurisdiction, be it a state, a city, what have you, is going to have its own unique features and advantages and challenges.

[00:07:17] But a lot of the broad concepts remain the same. And that is true in Utah as well. You know, something that You mentioned as you're calling. I mean, I think it's actually really important point, and is a note that I made to myself to mention here is that one of the big advantages of wastewater surveillance that, you know, we thought was going to be true when we started this very early on in the COVID epidemic certainly borne out.

[00:07:44] And I think remains one of its chief advantages is that is extremely efficient way to gather a large amount of data you know, when you just look at the raw numbers in terms of dollars, it's not the cheapest program out there, but if you think about trying to gather as much data as we're getting via wastewater surveillance via any other mechanism, I mean, it would be outrageously expensive if it was feasible at all, which is just not.

[00:08:11] So aside from the fact that it's not possible to get that data via other means, realistically speaking, it would be massively more expensive. So that value proposition is a huge advantage for wastewater surveillance. It's just massively efficient. You know, linked to that, and again, something that we, I think, relatively early on thought was going to be a real benefit for it.

[00:08:38] And it again has certainly borne out and is now one of his chief advantages is that and I kind of alluded to this already is that it is a very useful mechanism for generating data where either little or sometimes no data exists, either in a particular geography or a particular time or some combination thereof, and also in places and times when generating additional case level individual level data just isn't feasible, which is a lot of places we saw that even at the height of the COVID pandemic here when you know statewide we were getting something like 30, 000 ish.

[00:09:20] test results, individual test results per day. There are still fairly large disparities in who was getting tested, who was willing to be tested and who had reasonable access to those testing resources. And that was at the best it's ever been. It's not going to be like that and certainly not anytime soon.

[00:09:40] Possibly not. In this generation. And so there's still a need to get data so that we can appropriately inform public health actions, as Amy was saying, because we still need to take these actions. We still need to protect the public's health and figure out what we're going to do and where and how. And if we don't have data to base that on, we're just going to be basing it on assumptions and preconceptions.

[00:10:07] And so having this ability to get data from these areas and these populations that it can traditionally be very difficult to get any sort of reasonable or generalizable data from. Becomes massively powerful and extremely useful. And again, this is something that Amy touched on as well.

[00:10:27] Another real benefit for it. You know, certainly at the national level. Absolutely, at the state level and smaller is that it gives a more accurate idea of what you might think of as the full burden of a particular disease within communities by full burden, I mean, not just cases that are severe enough that somebody sought medical attention or was severe enough that they went and got tested.

[00:10:54] It captures asymptomatic folks, people who have very mild symptoms or as well as those who are more severe. And a lot of other data streams, they're definitely skewed towards that more severe end. That doesn't mean they're not still useful. A lot of times, these are still, those are the populations that we're potentially most concerned about because they have the most severe disease, but we are still very interested in the broader picture as well, not just to gain a better understanding of disease dynamics within populations at given times, but also because disease within these, the people that have more severe diseases or more susceptible to severe disease, they come from somewhere and it very well may be somebody who doesn't even know that they're infected. That happens all the time. We saw that in COVID constantly. And so having this data source that is sort of agnostic, you know, to a large extent between what level of symptoms you may be experiencing, if any at all, is a real benefit for it.

[00:11:50] And it becomes very complimentary with other data sources that are maybe more geared towards those more severe cases.

[00:12:00] Max Herzog: Thanks so much, Nathan. Yeah, really helpful to get that perspective and see sort of how these dynamics are playing out at the state level. I want to turn now to Raul, you know, as a representative of a utility, really curious how these value propositions, these technologies are playing out and being used, within, you know, a given community.

[00:12:23] Raul Gonzalez: Yeah, thanks. Those were two great, detailed responses from them, but, you know, at, at the hyper local level. HRC, the utility I work for, we really do this and started doing this to serve our local community. So in 2020, when we started, we really thought that this could be like a public health data stream, not just for like our ratepayers, but also the smaller local public health groups, within our service area. And, as I just mentioned in early 2020, when we started, we got buy in, shortly afterwards, from our community and actually started to, receive requests to assist in really local projects, so we kind of went from, you know, kind of creating our own data set and program at the utility, to working with kind of local partners in their data needs.

[00:13:32] And, so we've responded to projects, at levels, like, the correctional facility level, like, Monitoring wastewater from inmates to military barracks. They've reached out to us, to assist in generating this, like, data stream, and even have done some dorm testing early on.

[00:13:59] So, for us as utility members, you know, we really found our role in supporting these type of projects at this really local level and have seen ton of successes across not just like, facility level projects, but down and, kind of really niche areas like military barracks and things like that.

[00:14:29] Max Herzog: Great. Thanks so much, Raul. Yeah, hoping that this is really putting together a picture for folks about how these data are collected and and put to use, you know, at the community level and then aggregated and deployed for further value at each successive level of government really exciting to see how these sets are being integrated and pulled together and used to help people in these various ways.

[00:14:54] Now that we have sort of a base level of understanding of what this area of work looks like, and why we're doing it, perhaps we can turn to some of the challenges and limitations currently facing this field of work. I'm curious what barriers you all see to efficient, impactful, and safe implementation of wastewater surveillance. And I want to turn this one again, I think 1st to Amy to get your perspective.

[00:15:21] Amy Kirby: Thanks, Max. I want to pull out a word out of that that I think is not addressed enough. And that's safe. I think we all know that there are a lot of pathogens and wastewater, but what we have seen in the last, what are we up to now? 3 years since 2020. We've had wastewater surveillance on a large scale for COVID, and then in the past year on a large scale for MPox both of which are pathogens that we didn't have information on their infectivity out of wastewater. And so one of the things that we prioritize at CDC is when we start thinking about testing for a pathogen in wastewater, we need to understand what the implications are for that, for the people that are going to be.

[00:16:05] Directly exposed to wastewater, hopefully with all of the right  PPE, but what is the correct PPE for these pathogens? So how do we provide the best recommendations to wastewater workers that may be down actually in the sewers and exposed to Wastewater? What do we need to do to protect our laboratory workers that may be doing concentrations that could potentially aerosolize some of these pathogens out of Wastewater?

[00:16:32] And so we always work to understand that, we got extremely lucky with COVID that even though we detected at very high levels and wastewater. It looks like the vast majority of that is non infectious virus. And so the risk of infection from wastewater exposure to COVID is very, very low. Similarly, we think the risk for MPox is quite low, not necessarily because the virus is not infectious, but because it's still a fairly rare infection and it.

[00:17:03] It's not as transmissive as COVID is so we're in good shape and have been able to say, you know, all of the PPE that you would use for your standard, wastewater, job hazard appropriate, PPE will work. We've been able to develop biosafety for our laboratory professionals to keep them safe, but it is something that as we continue to move forward, particularly as we think about expanding wastewater surveillance to really be part of our readiness program for pandemic preparedness. You know, what? Heaven forbid is the next COVID coming down the line? How are we going to prioritize understanding the infectivity there? Because I think it's really easy to dive in and, get really excited by science and what it can do. But we want to make sure that everybody is as safe as they can be doing that work.

[00:17:56] Max Herzog: Absolutely. Yeah, keeping us anchored in that core values is absolutely critical. Really appreciate that perspective.

[00:18:06] I want to turn now to Anna, you know, at WEF, you're interacting with a whole host of utilities, research institutions. What are you seeing as some of the barriers to implementation for wastewater surveillance from that perspective?

[00:18:21] Anna Mehrotra: Yeah thanks. And thanks, Max, for having me on the panel today. So at WEF, we've been thinking and talking a lot about barriers, and in particular, barriers to sustainable utility participation in these programs, because obviously they can't exist, right, without the utilities being willing to provide samples.

[00:18:42] A lot of our thinking and discussion around this barrier topic has been going on within a series of in person workshops that we're running in collaboration with the CDC news team and also with EPA in the 10 EPA HHS regions around the country kind to capture the whole geography of the of the U.S.

[00:19:03] And in these workshops, we bring together public health and wastewater professionals to talk about barriers, and we've executed seven of these workshops so far, and together as a group with nearly 300 participants, we've identified 700 barriers or more than that, actually, and some of those are duplicates, but you get the idea, there are a lot of barriers, and we've taken some time to kind of organize those barriers into different categories, so I wanted to offer up some information on the top three barrier categories that we're seeing so far.

[00:19:39] The biggest, number one, is the, what I call the but why barrier. But why do this if the data aren't being used for public health action? But why do this when the COVID, you know, public health emergency is over? But why do this if this has nothing to do with meeting our permit limits? And those are all really great questions that it turns out have some good answers.

[00:20:02] And we heard some of those answers already from Nathan and Amy, you know, there's health departments are using the data, sometimes in more subtle ways than utilities might expect, or the public might expect. And there's so much more to wastewater surveillance than COVID. And, you know participating in these programs is aligned with the utility's mission to protect public health. But the fact that these questions come up, and that they do have answers really speaks to the need for better messaging, communication and education on this topic. And WEF can certainly play a role in that effort.

[00:20:41] So that was the first category, the but why. The second one is related to data. So this is everything, you know, all the uncertainty around the many kinds of aspects of data use and sharing. So uncertainty about who should get access to the data. What the utility's role is in interpretation of the data, and whether we can really trust the data, knowing what we all know about, the complexity of the wastewater matrix, and also kind of the variability of conditions within any given collection system, and from one collection system to another.

[00:21:16] Right. So that's the second category. And the third one I just wanted to offer up relates to staffing. This is the one we probably think of as being the most common barrier, but it's actually a little bit down on the list after the but why and the data, but staffing barriers are just what you would expect, you know, mostly refers to the general lack of adequate personnel to take on the additional tasks associated with collecting samples packaging those samples up and then working with their public health partner to get them to the right lab, which is often a different lab than what the utilities already using for ongoing compliance sampling.

[00:21:52] There's a lot that goes into, you know, determining how long that effort will take on the utilities part. You know, what type of sample are you collecting? Are you relying on a courier or do you have to take your sample to a FedEx drop off? But it can be anywhere from 20 or 30 minutes to a sample, up to three hours per sample or more, so depending on how short staffed your treatment facility is, this can be a substantial investment of time.

[00:22:19] Max Herzog: Absolutely. Thanks for sharing those thoughts. And really, you know, we're fortunate in the industry to have this kind of level of sort of meta analysis to understand what are the things that we need to be working on to be really greasing the wheels and enabling this work to scale and accelerate, to turn now to Nathan, you know, from the perspective of a health, state health department, you know, you're kind of one of the users of these data. I'm wondering. What barriers are you running into in those pursuits?

[00:22:55] Nathan LaCross: There are certainly some, which is unsurprising. It's a very new field. So, you know, figuring out what is one of the best practices for generating the data for analyzing data for disseminating, communicating it, visualizing it, interpreting it, all of that is still very much evolving pretty rapidly.

[00:23:17] I will say we are, I think we have a much better idea now that we did even a year ago. Say at least I do some others, maybe then a little bit further ahead than myself would not be surprised and, you know, one of the real benefits. This isn't a direct answer to the question, but, you know, it's something I think to really emphasize with wastewater.

[00:23:35] And I think this panel is actually a good illustration of that. There's a really active community. around wastewater surveillance, which has been massively helpful. You know, I've been able to ask questions of both folks at the federal level, but also colleagues in other states and other jurisdictions and vice versa.

[00:23:54] Questions have come back to me. And that level of community has been extremely helpful for figuring out. Ways of best interpreting and using these data. But we don't have it all figured out by any stretch of the imagination. I do want to preface all of that second preface. I guess you could say it is, just by saying that even though there are a lot of these really big open questions still, that doesn't mean that the data.

[00:24:21] Isn't usable or useful. It is. It was usable and useful two and a half years ago. I mean, amazingly early on, it proved it's to my mind, at least with our data and a lot of others I've talked to as well. Very, very early on in the pandemic. We saw really obvious and clear correspondence between changes in our wastewater levels and then subsequent changes within case rates within percent positivity within hospitalizations, all sorts of things.

[00:24:47] So to my mind, it went a long way towards proving itself years ago. Now we're figuring out some of the more subtle aspects. So some of the open questions, and there's quite a few, are one of them at least is around what you might think of as confounders. They're not really necessarily confounders, but It's not an inappropriate term.

[00:25:07] These are things, other things that affect the data that we may or may not have data on. Usually we don't, but they can have that potentially strong effect in the data and this changes our interpretation and perception of what it's telling us when really it's some other, one of these other tangentially related factors that's really  the root cause there.

[00:25:34] These are things like industrial input obviously that can be a whole host of things. That's a hugely broad term, but there's a lot of stuff that could be in that can, as an example, degrade the genetic material we're trying to detect. And that's going to change over time. It's gonna be different from site to site and from time to time.

[00:25:53] The temperature of the wastewater stream, how long it takes to get from a given home to the sampling point, how long it then takes to get from the sampling point to the actual laboratory and what temperature that's been kept that, and then there's a whole host of population level factors as well, You know, we don't least I don't and I know that's an open question with a lot of my colleagues have a good sense for which of those are the most important, which ones would be really paying attention to if we figure that out.

[00:26:25] How do we get data on some of those? We don't typically have a lot of data on much of that. And if we have data, how do we use the data to make the results more accurate? I guess you could say, so that's certainly one open question, but again, even essentially taking into account very little, if any of that, the data is still usable and useful.

[00:26:47] Just want to emphasize that, you know, another thing to consider with a lot of these factors that are really kind of specific to a site. They differ from site to site. They kind of change the range of data that you're likely to see at any given time. A lot of times the trends will remain roughly the same, but the range of data that you might see can be different from site to site.

[00:27:09] That really complicates the aggregation of data. So you might want to look at data, not just from a given site, but maybe all sites within a county. Or all sites within a state or all sites within a region of the country, as you know, thinking about from the CDC level, and that becomes really difficult, or at least more difficult when you have all these other factors that we don't really care about, but they affect the data, and we don't really understand yet precisely how best to deal with them.

[00:27:36] I think we have, we're starting to develop some methods. They're not perfect. I think in a couple of years, again, once again, we have a much better idea, but those are some of the open questions. You know, I kind of touched on this a little bit as well, early on, I said the data is usable and useful. One of the ways we were able to do that was really benchmarking against existing traditional data sources.

[00:27:58] So you might think it's the gold standard. All data sources have their own problems and limitations and strengths. But, you know, really quite quickly, as I mentioned, wastewater data really showed pretty strong correspondence to other individual level data sources like case rates or hospitalization rates.

[00:28:20] And that's something that is really useful going forward to even now that you know, the testing, the individual testing situation is vastly different and it's vastly less reliable as a data source itself, which makes wastewater data and other similar data sources like, that aren't reliant on individual testing, like syndromic surveillance data, very much more useful.

[00:28:41] You know, this isn't in isolation and it shouldn't be in isolation should be combined ideally with as much other data as you can manage to gather about a situation because each is measuring a different aspect of the overall situation we're trying to better understand.

[00:28:58] Max Herzog: Absolutely. Thanks for sharing that perspective Nathan I mean it makes sense right like these are some of the questions that we asked about. Kind of, make data sets actionable in general. It's like, how do we affiliate metadata with those data? How do we benchmark sets that range across a wide variety of contexts so that they can be compared or integrated, but still carry that initial original context with them? And with wastewater surveillance, it makes sense that it would be that much more challenging because you're sampling across such a broad area and you don't, you're not able to gather some of those contexts as easily.

[00:29:33] But exciting to hear that work trying to hone in on those components. In general, this is really helpful to hear about. Kind of the variety of barriers that you all are seeing across. Across the field, but also a lot of the emerging efforts to address them. I think we can turn now towards our last question, which is really looking more towards that future.

[00:29:58] You know, as we work to address these barriers, what could the future of wastewater surveillance really look like? What would successful implementation at scale of this technology look like for the water industry, but also for society in general? And, I think, I want to turn first to Anna to get your perspective, on this, but again, want to remind folks to pop those questions in the Q&A, because we will be turning to Q&A, shortly, but Anna, what's your take on sort of the future of wastewater surveillance?

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[00:30:33] Anna Mehrotra: Yeah, that's a small question. Well, so, you know, it's necessarily going to be a portfolio of different approaches to, sample collection, analysis, interpretation, data, communicating those data out. And that's what's so great about the National Wastewater Surveillance System is that each jurisdiction uses its own approach.

[00:30:54] And as Nathan was speaking to, you know, learn, they learn from each other, right? So, in other words, it's going to look varied, the future of wastewater surveillance. But, if I wanted to touch on one thing that doesn't come up that often. So, and it relates to analytical methods, which really, Amy or Nathan or Raul should be speaking to, but I'm going to speak to it anyway.

[00:31:15] If I'm reading the tea leaves correctly, the future of laboratory analyses for wastewater based infectious disease surveillance is digital PCR and sequencing and decoding being done in public health labs or in academic or commercial labs, you know, partnering with health departments, in these programs.

[00:31:36] But there is this class of rapid analytical methods that may not be as sensitive as DPCR, but could potentially be the best, or maybe the only way for remote locations. To enjoy the benefits of wastewater surveillance. So by remote, I mean really any community that has a good place to take an untreated wastewater sample.

[00:31:59] So at a small treatment facility, maybe a community septic system, but would have a really tough time getting that sample to the right lab. So think about, you know, a town or village in Alaska that is only accessible by plane. Or a rural community in the lower 48 that is a two hour drive to a FedEx drop off location.

[00:32:22] There are more of those than you might think so right now there is a QPCR based rapid testing method that requires less than a milliliter of wastewater and gives, you know, quantitative results within 45 minutes. Right now it has the capability for SARS CoV 2, RSV, and flu. So this method is still being evaluated by the News Center of Excellence in Houston, by a pilot that WEF is running, in collaboration with the news team.

[00:32:53] So stay tuned for more on that. That's the CEPHEID gene expert method. But there are other testing methods on the horizon that may or may not end up being suitable for on site rapid testing of pathogen markers in wastewater. So these include something called an MG LAMP approach, and then there are also ELISA based approaches that may end up being useful.

[00:33:17] So in case you're wondering, MG LAMP stands for Membrane Based In gel loop mediated isothermal amplification and Eliza is an enzyme linked immunosorbent assay, so not PCR and actually there was a viewpoint in the journal Nature Water, last month that called for in field automated methods, for wastewater surveillance that incorporate, you know, nucleic acid extraction analysis and data communication all in one package.

[00:33:48] They called these an end to end or E2E solution. These E2E solutions don't exist yet. But they may one day, and it's a little unclear how results from an E2E solution like that or, you know, non PCR rapid testing methods would fit into the fabric of the National Wastewater Surveillance System, that the jury's still out on that, but I do think these rapid methods are worth keeping their eye on and certainly waffle continue to do that.

[00:34:19] Max Herzog: Yeah, it's really interesting to think about the emergence of those types of solutions. I feel like the adoption of innovations in this industry often follows this trend where those higher capacity utilities are able to push forward the innovation, but then thinking about how that, you know, spread out trickle down.

[00:34:36] However, you want to frame that to those smaller, more rural utilities that also could benefit from this information. And the question of how you integrate those data back in, then it obviously circles back to Nathan's last comment of how do you benchmark and integrate these really diverse data sets, but critical to be able to collect that data to be able to start to ask that question. Speaking of sort of bringing things to that local context, I'm curious, Raul, from your perspective in the municipality space, what does sort of the future of this look like for you, how do you see the scaled implementation of wastewater surveillance working at Hampton Roads?

[00:35:18] 

[00:35:21] Raul Gonzalez:I feel like I'm going to use HRSD as an example of how I think a utility can take this. And with the caveat that we're, you know, a good size utility. That does have resources for, research and development, but, and I actually mentioned this earlier, about linking wastewater surveillance to our mission.

[00:35:48] So HRSD has, has taken a very,I'll say aggressive approach at this and has actually reshaped our mission and vision to actually include, public health and it doesn't explicitly say wastewater surveillance, but, you know, we're kind of alluding to this type of work. So we've made it like a priority where now it's a part of my job duties and a whole section, like a whole group of ours.

[00:36:21] Duties to do this moving forward like it's so for us, we've kind of committed and saying like, hey, there's been a lot of positive response and action on our data. So we're not going to stop. So we've kind committed to doing this locally. Also, we're continuing to strengthen these relationships that have been formed in the last few years through wastewater surveillance.

[00:36:49] So, you know, we continue to really be proactive in meeting with our local health departments, local municipalities and stay health departments on, like, a weekly basis. Like, we still continue to make sure that we're communicating that we're moving. I mean, that we're meeting.

[00:37:09] So that we are responsive to any needs that they have, where we can assist. Also we're starting to kind of rethink our workforce within our group of scientists. You know, we're starting to realize, okay, you know, we probably need to kind of solidify, or we need to start rethinking, staffing, especially if we're going to have this kind of focus.

[00:37:44] So we need to hire more employees from, you know, the public health sector and, and more environmental microbiologists to kind of support, the work that we do internal and, and the work that we support, that's kind of external, like bigger scale projects. And also investing into technology.

[00:38:09] I know Anna just talked about things like, uh, instrumentation and technology. But, you know, if we're going to have a seat at the table and if we're going to help in data interpretation, then we really need to understand the technology that's creating this data. So everything from digital PCR, which we've been using for like nine years now.

[00:38:35] To sequencing. So we've invested in multiple sequencing platforms in a house and have started to, actually generate data, so that we can understand it so that we can, you know, help in that interpretation, so, you know, I think all of those things, probably not at all  levels that that we're doing it, but can be done at other, you know, kind of local utilities.

[00:39:07] Max Herzog: Absolutely, and it's always going to be, you know, utilities like Hampton Roads that are able to sort of chart that path and set the example. And then, you know, we can figure out as an industry, how those lessons can be implemented in other contexts. So really exciting to hear that level of commitment and all the possibilities, not just for implementing the technology for impact, but the ways that it can catalyze the development of new partnerships.

[00:39:30] It's really exciting just to round us out here on sort of the prescriptive portion of our discussion, you know, CDC has been at the forefront of a lot of this work. You have sort of the highest. Level view of what this is looking like for our country and for society in general.

[00:39:51] I'm curious. You know. Amy, what do you see, you know, implementation of this looking like in the future of wastewater surveillance?

[00:40:01] Amy Kirby: Yeah, well, 1st, I just have to say role answer makes me so happy and I'm thrilled to hear the changes at HRST. I hope that other utilities will be able to follow their lead.

[00:40:12] So, to get to your question, Max, as we're thinking about transitioning from, like. Very young response oriented, emergency state COVID program, to a sustainable long term program. There are a few things that we're focusing on. So, the 1st is the move towards standard protocols. So, early in the pandemic, there were lots of methods and it wasn't clear that one was outperforming the other.

[00:40:38] And so we didn't want to. Lock the system into something that might not work in the long run. And so we sort of let that all play out. It's now become clear that there are some methods that are much more effective than others. And so we are developing standard protocols. As Anna said, they are digital PCR based.

[00:40:55] And so the whole system will be transitioning over to digital PCR over the next few years. We are validating in-house protocols for those and they will be made available, totally open source, probably by the end of this year. We hope to be implemented within our centers of excellence early next year, enrolled out to the full system in summer of 2024.

[00:41:22] As part of that, we are expanding to other pathogens. So, looking at. What other types of pathogens could we improve surveillance and understanding by using wastewater surveillance? And those were very hard decisions to make. It is amazing how many things you can detect in wastewater, things that you may haven't thought about before.

[00:41:46] A lot of respiratory pathogens are detectable this way AR jeans, all kinds of things you could look at. So we really had to be very rigorous to understand the technical challenges. And again, what is the action? How are we going to use this data to improve public health? and so we have converged on a panel of 24 targets.

[00:42:11] I will not list them all here. I'll just say there's other respiratory pathogens. So influenza is a respiratory syncytial virus. We're adding some food borne pathogens. So norovirus campylobacter, shiga toxin producing E. coli, which is the 0157 type strains, as well as adding the emerging fungal pathogen candida auris, sort of an emerging pathogens panel, and then a panel of antibiotic resistance genes that are, deemed our threats by CDC, so we will be expanding to those.

[00:42:46] This is not a one and done approach. The composition of that panel will be reviewed annually by subject matter experts from across CDC to make sure that we're staying up to date on really the public health needs, for these different pathogens and that we are using this platform and this resource where it can be most impactful and most cost effective.

[00:43:10] Right? We don't want to get data just for data sake because that's not being good stewards of federal money. So where are we actually getting, cost effective, valuable surveillance data? as part of that. We are rethinking our sampling frame. So, for COVID, we wanted to sample everywhere, twice a week, as much as we could, because it was everywhere and moving quickly.

[00:43:34] for some of these other things, that really doesn't make sense. You don't need to sample twice a week for antimicrobial resistance. It is not changing that quickly. That is going to be wasted effort. So, what is the appropriate time frame? And as we move out of the full response mode, Is there a more effective sampling strategy that can give us the representativeness we want while still being cost effective.

[00:43:58] And then finally, I alluded to this earlier, but I really want to end on this. Wastewater surveillance is going to be a core part of our readiness for pandemic. Preparedness and response for whenever the next one comes to us and a big part of that is building a system that is robust and sustainable that we don't have to turn it on again because I recognize a lot of names on this call.

[00:44:28] And this is only a fraction of the people across the country that are helping us get this system going. If we shut it down and have to turn it on again for another pandemic. We will be behind the eight ball from the very beginning. So we want to have a system that is sustainable that has a streamlined workflow that we can manage even in public health peace times so that when the non peace times come, we can implement it very quickly and get all of the advantages that we, I think, Nathan, described so nicely of wastewater surveillance data.

[00:45:05] Max Herzog: Thanks so much, Amy, and thanks so much to our panelists for a really comprehensive discussion about this area of work. That's really quite exciting to see it emerge and grow over the past few years. We do have a few minutes left now and I want to turn to some of the questions from our attendees.

[00:45:24] 1st up, we have a question. About whether anyone on the panel has experience working with private partnerships. On wastewater analytics, maybe, or other panelists that folks have thoughts on what those types of partnerships would look like for y'all. 

[00:45:42] Amy Kirby: Sure. So we have, in addition to our state supported system through direct funding to the State Departments help. We also have a large commercial contract for wastewater testing right now. That is with bio bot, although it's been with other companies in the past and all of those companies do their own analytics and that has been very useful. I think we're still trying to, You know, the core analytics are pretty clear for a site.

[00:46:09]I think Nathan addressed this earlier when it gets hard is when you start trying to aggregate that data up to the county level to the state level to the national level. Lots of ideas for how to do that we are evaluating all of those at CDC and trying to decide whether or not they are useful. I think the clearest way to think about this is if we look at COVID surges that have happened in the past.

[00:46:35] It's not like the whole country goes up and then back down at the same time. We see this wave generally coming out of the northeast and then rolling down to the southeast and across the country. Even if we do it by region or state, you will have that period where half of the stage is going up and half hasn't come up yet.

[00:46:54] And so you lose that early warning capability of wastewater when you start aggregating up. There's some value to that aggregation, but we want to make sure we're aware of the costs that come with that too. And so we know how to interpret that data. So we are working with them really with everyone that's doing these type of analytics and trying to figure out how to improve those to get the most value out of this system.

[00:47:23] Max Herzog: Great, thanks so much, Amy our next question here is about, you know, the similarities or differences between wastewater sampling, oh, I'm sorry, I see Anna chimed in here in the chat do other folks have have responses to that collaboration with. Private partnerships question. Sorry for moving on so quickly.

[00:47:48] Other folks. Oh, I'm sorry. I see. I'm sorry. I'm looking at the chat and facility at the same time and getting a little a little mixed up. So speaking to the next question, are the sampling protocols for wastewater sampling the same or similar as they might be for groundwater or surface water monitoring?

[00:48:10] You know, specifically things like field trip samples, replicates. And other QA, QC, kind of components applied do samples need preservation or special handling? Do any folks feel like they have experience to speak to kind of those nuances there. 

[00:48:31] Nathan LaCross: Raul might be the best one to speak, but I'll give it a shot 1st, then he can correct where I get it wrong. I don't have a great deal of familiarity with at least I picture groundwater surface water sampling in terms of sort of like environmental remediation. I did some work in that field a few years back but not in the actual sampling aspect.

[00:48:52] At least the way we're doing it doesn't typically have that same, certainly not the same sort of potential for litigation, at least not yet fingers crossed, never ever. So a lot of the ways that they're taking samples in the more environmental aspects of things really necessary. So, for example, we're not really taking replicates.

[00:49:14] Currently, we're getting like 250 mils of a wastewater sample, and then we'll do PCR replicates based on the sample. We're not taking multiple samples. In no small part, that's to also reduce the burden on our partner facilities. We want to, like Anna was talking about previously, we want to get that down as low as we can get it so that it's as sustainable as we can make it.

[00:49:36] Preservation wise, what we do is we keep everything as cold as we can to try to limit the degradation of the genetic material, and then get it to the lab as quickly as possible. Which is sometimes overnight, but as quick as we can manage it.

[00:49:52] Max Herzog: Thanks so much, Nathan. Anything you'd add there, Raul? 

[00:49:55] Raul Gonzalez: I'll just add that if we're talking about like micro in general, I would say the methods are pretty similar, As in there's like a concentration step and a lot of the transport and QAQC stuff is very similar on some of our local projects we do a lot of that.

[00:50:17] We do take a lot of that QAQC from the regulatory side and add it like trip lengths and stuff like that and duplicates as was mentioned. If we're talking about just like, if you're already familiar with molecular analysis for all those other environmental samples, I think it's kind of the same.

[00:50:33] There's always a concentration step, there's a DNA extraction step, or RNA extraction step, or just nucleic acid extraction set, and then like PCR, that part. Fairly consistent. I think one of the reasons why we pivoted really easily to Wastewater surveillance is because we're already doing micro and molecular methods for environmental samples. And so we just kind of pivoted to that and used the same type of approaches.

[00:51:00]  Nathan LaCross: And I'll just very, very briefly add that, you know, Not certainly not all of the things like replicates and other sort of QAQC stuff, is geared towards this, but some of it is towards sort of general representativeness of the sample in terms of capturing the situation most, but not all by any stretch, but most of the time wastewater samples are gonna be some flavor of roughly 24 hour composite sample.

[00:51:24] Unsurprising to most folks here, I'm sure and that I think does go a long way towards that representativeness.

[00:51:33] Max Herzog: Thanks very much for sharing those thoughts. Probably our last question here today, depending on how quickly we are, we respond, but, are there any plans or considerations that folks are aware of to integrate chemical analysis? ]into N. W. S. S. for narcotics, pharmaceuticals, endogenous compounds, other components folks are aware of any, any thinking around that type of  approach.

[00:52:00] Amy Kirby: Definitely lots of thinking and lots of discussion around that. I think. I know Adam, the asker of this question, will not be surprised here.

[00:52:12] This is very polarizing. There are some people that are very much in favor of it and some that are very much not. And I think what that's really telling us is that there are unresolved issues behind this that we need to address first and those fall into two categories. So one is, What is the application and public health use of this data?

[00:52:32] and so a lot of it has been focused on trends again. So if you see, for example, sentinel going up in a community, you know, how would you respond to that? and so there are various people on different sides of that. I think the use that.is the clearest to me is using chemical testing to detect new street drugs in a community.

[00:52:58] So xylazine we have seen, showing up in communities, as an adulterant of, heroin and fentanyl actually, and so looking to see when that moves into a community could be a very good use. But again, making sure that there is an action tied to that, and that we understand how to interpret that data.

[00:53:19] What else is adding to that signal other than the use that we are most interested in. So, that's number one,  number two is, there are lots of questions around the ethics of this type of testing and frankly, around wastewater surveillance overall, that just get heightened when you're talking about, potentially, an illegal behavior, like illicit drugs.

[00:53:42] and so we need to be really clear with what the ethical framework is, how this data is collected. How we share it, how we make it available, we want to be very transparent and everything that we're doing. So, making sure that when we share the data, there are some guardrails around it. So that it's not used in ways that don't promote public health.

[00:54:04] That may actually be damaging to public health. And we also need to keep in mind that this whole program is voluntary. And so community acceptability is really important. There have been some studies. showing the community acceptability for wastewater surveillance for infectious diseases is quite high over 90%.

[00:54:24] But when you ask about drugs, even opioids, which can be legally prescribed, the acceptance drops to 60%. So, we need to approach this very carefully, but it's definitely something that CDC is thinking about and we are moving towards some early pilot studies of this to try to understand what the use cases might be. And again, how we can put those guardrails up around the data to make sure that it is done in a way that is ethical and acceptable to the community.

[00:54:59] Max Herzog: Absolutely really appreciate those perspectives and those thoughts, Amy, really interesting to think about, not just. Or not interesting, but it's really compelling to hear the way that the deployment of this technology is really anchored to community benefit and benefit to society and thinking about, you know, can we do this as one question?

[00:55:19] And should we do this as another question? And it's always good to hear those things being considered during the development and deployment strategy of new technologies. I don't think we have quite enough time to answer any other questions. So I hope folks will join me in thanking our panelists for being a part of this conversation today, really, you know, incredibly educational for me.

[00:55:43] And I'm sure many of our attendees, who aren't as deep into this space to learn all the ins and outs of what this conversation is looking like, how it's been impactful over the past few years, what it may look like in the future. And it's really, it's inspiring to see folks that are doing this work, and really encouraging as well.

[00:56:05] I do want to close out with a quick plug for our next water data forum session, which we will take, which will be taking place in September. We haven't scheduled a specific date yet, but if you attended today. You will get email notification about this.our next session will be focused on the digital twins readiness guide, which I believe has a focus on water and wastewater utilities.

[00:56:26] So, if you're interested in that topic, please do attend and please do stay tuned in for future sessions as well on topics such as this. With that, we're at the hour. So I want to thank everyone for taking the time here on Friday afternoon to be with us for Water Data Forum. One last thank you to our panelists, and I hope you all have a great, great rest of your day and a great weekend.