Online dashboards for SARS-CoV-2 wastewater data need standard best practices: An environmental health communication agenda.

The COVID-19 pandemic has highlighted the benefits of wastewater surveillance to supplement clinical data. Numerous online information dashboards have been rapidly, and typically independently, developed to communicate environmental surveillance data to public health officials and the public. In this study, we review dashboards presenting SARS-CoV-2 wastewater data and propose a path toward harmonization and improved risk communication. A list of 127 dashboards representing 27 countries was compiled. The variability was high and encompassed aspects including the graphics used for data presentation (e.g., line/bar graphs, maps, and tables), log versus linear scale, and 96 separate ways of labeling SARS-CoV-2 wastewater concentrations. Globally, dashboard presentations also differed by region. Approximately half of the dashboards presented clinical case data, and 25% presented variant monitoring. Only 30% of dashboards provided downloadable source data. While any single dashboard is likely useful in its own context and locality, the high variation across dashboards at best prevents optimal use of wastewater surveillance data on a broader geographical scale and at worst could lead to risk communication issues and the potential for public health miscommunication. There is a great opportunity to improve scientific communication through the adoption of uniform data presentation conventions, standards, and best practices in this field.

Stratified Simple Random Sampling Versus Volunteer Community-Wide Sampling for Estimates of COVID-19 Prevalence.

Objectives. To evaluate community-wide prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using stratified simple random sampling. Methods. We obtained data for the prevalence of SARS-CoV-2 in Jefferson County, Kentucky, from adult random (n = 7296) and volunteer (n = 7919) sampling over 8 waves from June 2020 through August 2021. We compared results with administratively reported rates of COVID-19. Results. Randomized and volunteer samples produced equivalent prevalence estimates (P < .001), which exceeded the administratively reported rates of prevalence. Differences between them decreased as time passed, likely because of seroprevalence temporal detection limitations. Conclusions. Structured targeted sampling for seropositivity against SARS-CoV-2, randomized or voluntary, provided better estimates of prevalence than administrative estimates based on incident disease. A low response rate to stratified simple random sampling may produce quantified disease prevalence estimates similar to a volunteer sample. Public Health Implications. Randomized targeted and invited sampling approaches provided better estimates of disease prevalence than administratively reported data. Cost and time permitting, targeted sampling is a superior modality for estimating community-wide prevalence of infectious disease, especially among Black individuals and those living in disadvantaged neighborhoods. (Am J Public Health. 2023;113(7):768-777. https://doi.org/10.2105/AJPH.2023.307303).

Estimating sewage flow rate in Jefferson County, Kentucky using machine learning for wastewater-based epidemiology applications

Direct measurement of the flow rate in sanitary sewer lines is not always feasible and is an important parameter for the normalization of data used in wastewater-based epidemiology applications. Machine learning to estimate past wastewater influent flow rates supporting public health applications has not been studied. The aim of this study was to assess wastewater treatment plant influent flow rates when compared with weather data and to retrospectively estimate flow rates in Louisville, Kentucky (USA), based on other data types using machine learning. A random forest model was trained using a range of variables, such as feces-related indicators, weather data that could be associated with dilution in sewage systems, and area demographics. The developed algorithm successfully estimated the flow rate with an accuracy of 91.7%, although it did not perform as well with short-term (1-day) high flow rates. This study suggests using variables such as precipitation (mm/day) and population size are more important for wastewater flow estimation. The fecal indicator concentration (cross-assembly phage and pepper mild mottle virus) was less important. Our study challenges currently accepted opinions by showing the important public health potential application of artificial intelligence in wastewater treatment plant flow rate estimation for wastewater-based epidemiological applications.

The Detection of Periodic Reemergence Events of SARS-CoV-2 Delta Strain in Communities Dominated by Omicron.

Despite entering an endemic phase, SARS-CoV-2 remains a significant burden to public health across the global community. Wastewater sampling has consistently proven utility to understanding SARS-CoV-2 prevalence trends and genetic variation as it represents a less biased assessment of the corresponding communities. Here, we report that ongoing monitoring of SARS-CoV-2 genetic variation in samples obtained from the wastewatersheds of the city of Louisville in Jefferson county Kentucky has revealed the periodic reemergence of the Delta strain in the presence of the presumed dominant Omicron strain. Unlike previous SARS-CoV-2 waves/emergence events, the Delta reemergence events were geographically restricted in the community and failed to spread into other areas as determined by wastewater analyses. Moreover, the reemergence of the Delta strain did not correlate with vaccination rates as communities with lower relative vaccination have been, to date, not affected. Importantly, Delta reemergence events correlate with increased public health burdens, as indicated by increased daily case rates and mortality relative to non-Delta wastewatershed communities. While the underlying reasons for the reemergence of the Delta variant remain unclear, these data reaffirm the ongoing importance of wastewater genomic analyses towards understanding SARS-CoV-2 as it enters the endemic phase.

Occurrence of Z-drugs, benzodiazepines, and ketamine in wastewater in the United States and Mexico during the Covid-19 pandemic.

Z-drugs, benzodiazepines and ketamine are classes of psychotropic drugs prescribed for treating anxiety, sleep disorders and depression with known side effects including an elevated risk of addiction and substance misuse. These drugs have a strong potential for misuse, which has escalated over the years and was hypothesized here to have been exacerbated during the COVID-19 pandemic. Wastewater-based epidemiology (WBE) constitutes a fast, easy, and relatively inexpensive approach to epidemiological surveys for understanding the incidence and frequency of uses of these drugs. In this study, we analyzed wastewater (n = 376) from 50 cities across the United States and Mexico from July to October 2020 to estimate drug use rates during a pandemic event. Both time and flow proportional composite and grab samples of untreated municipal wastewater were analyzed using solid-phase extraction followed by liquid chromatography-tandem mass spectrometry to determine loadings of alprazolam, clonazepam, diazepam, ketamine, lorazepam, nordiazepam, temazepam, zolpidem, and zaleplon in raw wastewater. Simultaneously, prescription data of the aforementioned drugs were extracted from the Medicaid database from 2019 to 2021. Results showed high detection frequencies of ketamine (90 %), lorazepam (87 %), clonazepam (76 %) and temazepam (73 %) across both Mexico and United States and comparatively lower detection frequencies for zaleplon (22 %), zolpidem (9 %), nordiazepam (<1 %), diazepam (<1 %), and alprazolam (<1 %) during the pandemic. Average mass consumption rates, estimated using WBE and reported in units of mg/day/1000 persons, ranged between 62 (temazepam) and 1100 (clonazepam) in the United States. Results obtained from the Medicaid database also showed a significant change (p < 0.05) in the prescription volume between the first quarter of 2019 (before the pandemic) and the first quarter of 2021 (pandemic event) for alprazolam, clonazepam and lorazepam. Study results include the first detections of zaleplon and zolpidem in wastewater from North America.

Nationwide public perceptions regarding the acceptance of using wastewater for community health monitoring in the United States.

To assess the levels of infection across communities during the coronavirus disease 2019 pandemic, researchers have measured severe acute respiratory syndrome coronavirus 2 RNA in feces dissolved in sewer water. This activity is colloquially known as sewer monitoring and is referred to as wastewater-based epidemiology in academic settings. Although global ethical principles have been described, sewer monitoring is unregulated for health privacy protection when used for public health surveillance in the United States. This study used Qualtrics XM, a national research panel provider, to recruit participants to answer an online survey. Respondents (N = 3,083) answered questions about their knowledge, perceptions of what is to be monitored, where monitoring should occur, and privacy concerns related to sewer monitoring as a public health surveillance tool. Furthermore, a privacy attitude questionnaire was used to assess the general privacy boundaries of respondents. Participants were more likely to support monitoring for diseases (92%), environmental toxins (92%), and terrorist threats (88%; e.g., anthrax). Two-third of the respondents endorsed no prohibition on location sampling scale (e.g., monitoring single residence to entire community was acceptable); the most common location category respondents wanted to prohibit sampling was at personal residences. Sewer monitoring is an emerging technology, and our study sheds light on perceptions that could benefit from educational programs in areas where public acceptance is comparatively lower. Respondents clearly communicated guard rails for sewer monitoring, and public opinion should inform future policy, application, and regulation measures.

Quantifying the relationship between sub-population wastewater samples and community-wide SARS-CoV-2 seroprevalence.

Robust epidemiological models relating wastewater to community disease prevalence are lacking. Assessments of SARS-CoV-2 infection rates have relied primarily on convenience sampling, which does not provide reliable estimates of community disease prevalence due to inherent biases. This study conducted serial stratified randomized samplings to estimate the prevalence of SARS-CoV-2 antibodies in 3717 participants, and obtained weekly samples of community wastewater for SARS-CoV-2 concentrations in Jefferson County, KY (USA) from August 2020 to February 2021. Using an expanded Susceptible-Infected-Recovered model, the longitudinal estimates of the disease prevalence were obtained and compared with the wastewater concentrations using regression analysis. The model analysis revealed significant temporal differences in epidemic peaks. The results showed that in some areas, the average incidence rate, based on serological sampling, was 50 % higher than the health department rate, which was based on convenience sampling. The model-estimated average prevalence rates correlated well with the wastewater (correlation = 0.63, CI (0.31,0.83)). In the regression analysis, a one copy per ml-unit increase in weekly average wastewater concentration of SARS-CoV-2 corresponded to an average increase of 1-1.3 cases of SARS-CoV-2 infection per 100,000 residents. The analysis indicates that wastewater may provide robust estimates of community spread of infection, in line with the modeled prevalence estimates obtained from stratified randomized sampling, and is therefore superior to publicly available health data.

Combining Community Wastewater Genomic Surveillance with State Clinical Surveillance: A Framework for SARS-CoV-2 Public Health Practice.

This study aimed to develop a framework for combining community wastewater surveillance with state clinical surveillance for the confirmation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants within the community and to provide recommendations on how to expand on such research and apply the findings in public health responses. Wastewater samples were collected weekly from 17 geographically resolved locations in Louisville/Jefferson County, Kentucky (USA), from February 10 to December 13, 2021. Genomic surveillance and quantitative reverse transcription PCR (RT-qPCR) platforms were used to screen for SARS-CoV-2 in wastewater, and state clinical surveillance was used for confirmation. The study results highlighted an increased epidemiological value of combining community wastewater genomic surveillance and RT-qPCR with conventional case-auditing methods. The spatial scale and temporal frequency of wastewater sampling provided promising sensitivity and specificity for gaining public health screening insights about SARS-CoV-2 emergence, seeding, and spread in communities. Improved national surveillance systems are needed against future pathogens and variants, and wastewater-based genomic surveillance exhibits great potential when coupled with clinical testing. This paper presents evidence that complementary wastewater and clinical testing are cost-effectively enhanced when used in combination, as they provide a strong tool for a joint public health framework. Future pathogens of interest may be examined in either a targeted fashion or using a more global approach where all pathogens are monitored. This study has also provided novel insights developed from evidence-based public health practices.

Standards to support an enduring capability in wastewater surveillance for public health: Where are we?

The COVID-19 pandemic highlighted a wide range of public health system challenges for infectious disease surveillance. The discovery that the SARS-CoV-2 virus was shed in feces and can be characterized using PCR-based testing of sewage samples offers new possibilities and challenges for wastewater surveillance (WWS). However, WWS standardization of practices is needed to provide actionable data for a public health response. A workshop was convened consisting of academic, federal government, and industry stakeholders. The objective was to review WWS sampling protocols, testing methods, analyses, and data interpretation approaches for WWS employed nationally and identify opportunities for standardizing practices, including the development of documentary standards or reference materials in the case of SARS-CoV-2 surveillance. Other WWS potential future threats to public health were also discussed. Several aspects of WWS were considered and each offers the opportunity for standards development. These areas included sampling strategies, analytical methods, and data reporting practices. Each of these areas converged on a common theme, the challenge of results comparability across facilities and jurisdictions. For sampling, the consensus solution was the development of documentary standards to guide appropriate sampling practices. In contrast, the predominant opportunity for analytical methods was reference material development, such as PCR-based standards and surrogate recovery controls. For data reporting practices, the need for establishing the minimal required metadata, a metadata vocabulary, and standardizing data units of measure including measurement threshold definitions was discussed. Beyond SARS-CoV-2 testing, there was general agreement that the WWS platform will continue to be a valuable tool for a wide range of public health threats and that future cross-sector engagements are needed to guide an enduring WWS capability.

Public Awareness of and Support for the Use of Wastewater for SARS-CoV-2 Monitoring: A Community Survey in Louisville, Kentucky

The majority of sewer systems in the United States and other countries are operated by public utilities. In the absence of any regulation, the public perception of wastewater monitoring for population health biomarkers is an important consideration for a public utility commission when allocating resources for this purpose. We conducted a survey in August 2021 as part of an ongoing COVID-19 community prevalence study in Louisville/Jefferson County, KY, US. The survey comprised seven questions about wastewater awareness and privacy concerns and was sent to approximately 35 000 households randomly distributed within the county. A total of 1220 adults were involved in the probability sample, and data from 981 respondents were used in the analysis. A total of 2444 adults additionally responded to the convenience sample, and data from 1751 respondents were used in the analysis. The samples were weighted to obtain estimates representative of all adults in the county. Public awareness of tracking the virus that causes COVID-19 in sewers was low. Opinions strongly support the public disclosure of monitoring results. Responses showed that people more strongly supported measurements in the largest areas (>50 000 households), typically representing population levels found in a large community wastewater treatment plant. Those with a history of COVID-19 infection were more likely to support highly localized monitoring. Understanding wastewater surveillance strategies and privacy concern thresholds requires an in-depth and comprehensive analysis of public opinion for continued success and effective public health monitoring. This study investigated the public awareness of and support for the use of wastewater for SARS-CoV-2 monitoring in Louisville, KY. The researchers found that awareness was low but support was strong. The researchers concluded that wastewater surveillance strategies and privacy concern thresholds require an in-depth and comprehensive analysis of public opinion for continued success and effective public health monitoring.

High-throughput sequencing of SARS-CoV-2 in wastewater provides insights into circulating variants.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) likely emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 548 were "novel" SNVs that had not yet been identified in the global clinical-derived data as of 17th June 2020 (the day after our last wastewater sampling date). However, between 17th of June 2020 and 20th November 2020, almost half of the novel SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.

The Rapid Assessment of Aggregated Wastewater Samples for Genomic Surveillance of SARS-CoV-2 on a City-Wide Scale.

Throughout the course of the ongoing SARS-CoV-2 pandemic there has been a need for approaches that enable rapid monitoring of public health using an unbiased and minimally invasive means. A major way this has been accomplished is through the regular assessment of wastewater samples by qRT-PCR to detect the prevalence of viral nucleic acid with respect to time and location. Further expansion of SARS-CoV-2 wastewater monitoring efforts to include the detection of variants of interest/concern through next-generation sequencing has enhanced the understanding of the SARS-CoV-2 outbreak. In this report, we detail the results of a collaborative effort between public health and metropolitan wastewater management authorities and the University of Louisville to monitor the SARS-CoV-2 pandemic through the monitoring of aggregate wastewater samples over a period of 28 weeks. Through the use of next-generation sequencing approaches the polymorphism signatures of Variants of Concern/Interest were evaluated to determine the likelihood of their prevalence within the community on the basis of their relative dominance within sequence datasets. Our data indicate that wastewater monitoring of water quality treatment centers and smaller neighborhood-scale catchment areas is a viable means by which the prevalence and genetic variation of SARS-CoV-2 within a metropolitan community of approximately one million individuals may be monitored, as our efforts detected the introduction and emergence of variants of concern in the city of Louisville. Importantly, these efforts confirm that regional emergence and spread of variants of interest/concern may be detected as readily in aggregate wastewater samples as compared to the individual wastewater sheds. Furthermore, the information gained from these efforts enabled targeted public health efforts including increased outreach to at-risk communities and the deployment of mobile or community-focused vaccination campaigns.

Evidence and magnitude of the effects of meteorological changes on SARS-CoV-2 transmission.

IMPORTANCE: Intensity and duration of the COVID-19 pandemic, and planning required to balance concerns of saving lives and avoiding economic collapse, could depend significantly on whether SARS-CoV-2 transmission is sensitive to seasonal changes. OBJECTIVE: Hypothesis is that increasing temperature results in reduced SARS CoV-2 transmission and may help slow the increase of cases over time. SETTING: Fifty representative Northern Hemisphere countries meeting specific criteria had sufficient COVID-19 case and meteorological data for analysis. METHODS: Regression was used to find the relationship between the log of number of COVID-19 cases and temperature over time in 50 representative countries. To summarize the day-day variability, and reduce dimensionality, we selected a robust measure, Coefficient of Time (CT), for each location. The resulting regression coefficients were then used in a multivariable regression against meteorological, country-level and demographic covariates. RESULTS: Median minimum daily temperature showed the strongest correlation with the reciprocal of CT (which can be considered as a rate associated with doubling time) for confirmed cases (adjusted R2 = 0.610, p = 1.45E-06). A similar correlation was found using median daily dewpoint, which was highly colinear with temperature, and therefore was not used in the analysis. The correlation between minimum median temperature and the rate of increase of the log of confirmed cases was 47% and 45% greater than for cases of death and recovered cases of COVID-19, respectively. This suggests the primary influence of temperature is on SARS-CoV-2 transmission more than COVID-19 morbidity. Based on the correlation between temperature and the rate of increase in COVID-19, it can be estimated that, between the range of 30 to 100 degrees Fahrenheit, a one degree increase is associated with a 1% decrease-and a one degree decrease could be associated with a 3.7% increase-in the rate of increase of the log of daily confirmed cases. This model of the effect of decreasing temperatures can only be verified over time as the pandemic proceeds through colder months. CONCLUSIONS: The results suggest that boreal summer months are associated with slower rates of COVID-19 transmission, consistent with the behavior of a seasonal respiratory virus. Knowledge of COVID-19 seasonality could prove useful in local planning for phased reductions social interventions and help to prepare for the timing of possible pandemic resurgence during cooler months.