A modeling pipeline to relate municipal wastewater surveillance and regional public health data.

As COVID-19 becomes endemic, public health departments benefit from improved passive indicators, which are independent of voluntary testing data, to estimate the prevalence of COVID-19 in local communities. Quantification of SARS-CoV-2 RNA from wastewater has the potential to be a powerful passive indicator. However, connecting measured SARS-CoV-2 RNA to community prevalence is challenging due to the high noise typical of environmental samples. We have developed a generalized pipeline using in- and out-of-sample model selection to test the ability of different correction models to reduce the variance in wastewater measurements and applied it to data collected from treatment plants in the Chicago area. We built and compared a set of multi-linear regression models, which incorporate pepper mild mottle virus (PMMoV) as a population biomarker, Bovine coronavirus (BCoV) as a recovery control, and wastewater system flow rate into a corrected estimate for SARS-CoV-2 RNA concentration. For our data, models with BCoV performed better than those with PMMoV, but the pipeline should be used to reevaluate any new data set as the sources of variance may change across locations, lab methods, and disease states. Using our best-fit model, we investigated the utility of RNA measurements in wastewater as a leading indicator of COVID-19 trends. We did this in a rolling manner for corrected wastewater data and for other prevalence indicators and statistically compared the temporal relationship between new increases in the wastewater data and those in other prevalence indicators. We found that wastewater trends often lead other COVID-19 indicators in predicting new surges.

Wastewater surveillance for bacterial targets: current challenges and future goals.

Wastewater-based epidemiology (WBE) expanded rapidly in response to the COVID-19 pandemic. As the public health emergency has ended, researchers and practitioners are looking to shift the focus of existing wastewater surveillance programs to other targets, including bacteria. Bacterial targets may pose some unique challenges for WBE applications. To explore the current state of the field, the National Science Foundation-funded Research Coordination Network (RCN) on Wastewater Based Epidemiology for SARS-CoV-2 and Emerging Public Health Threats held a workshop in April 2023 to discuss the challenges and needs for wastewater bacterial surveillance. The targets and methods used in existing programs were diverse, with twelve different targets and nine different methods listed. Discussions during the workshop highlighted the challenges in adapting existing programs and identified research gaps in four key areas: choosing new targets, relating bacterial wastewater data to human disease incidence and prevalence, developing methods, and normalizing results. To help with these challenges and research gaps, the authors identified steps the larger community can take to improve bacteria wastewater surveillance. This includes developing data reporting standards and method optimization and validation for bacterial programs. Additionally, more work is needed to understand shedding patterns for potential bacterial targets to better relate wastewater data to human infections. Wastewater surveillance for bacteria can help provide insight into the underlying prevalence in communities, but much work is needed to establish these methods.IMPORTANCEWastewater surveillance was a useful tool to elucidate the burden and spread of SARS-CoV-2 during the pandemic. Public health officials and researchers are interested in expanding these surveillance programs to include bacterial targets, but many questions remain. The NSF-funded Research Coordination Network for Wastewater Surveillance of SARS-CoV-2 and Emerging Public Health Threats held a workshop to identify barriers and research gaps to implementing bacterial wastewater surveillance programs.

Intensity of sample processing methods impacts wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes.

Wastewater SARS-CoV-2 surveillance has been deployed since the beginning of the COVID-19 pandemic to monitor the dynamics in virus burden in local communities. Genomic surveillance of SARS-CoV-2 in wastewater, particularly efforts aimed at whole genome sequencing for variant tracking and identification, are still challenging due to low target concentration, complex microbial and chemical background, and lack of robust nucleic acid recovery experimental procedures. The intrinsic sample limitations are inherent to wastewater and are thus unavoidable. Here, we use a statistical approach that couples correlation analyses to a random forest-based machine learning algorithm to evaluate potentially important factors associated with wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes, with a specific focus on the breadth of genome coverage. We collected 182 composite and grab wastewater samples from the Chicago area between November 2020 to October 2021. Samples were processed using a mixture of processing methods reflecting different homogenization intensities (HA + Zymo beads, HA + glass beads, and Nanotrap), and were sequenced using one of the two library preparation kits (the Illumina COVIDseq kit and the QIAseq DIRECT kit). Technical factors evaluated using statistical and machine learning approaches include sample types, certain sample intrinsic features, and processing and sequencing methods. The results suggested that sample processing methods could be a predominant factor affecting sequencing outcomes, and library preparation kits was considered a minor factor. A synthetic SARS-CoV-2 RNA spike-in experiment was performed to validate the impact from processing methods and suggested that the intensity of the processing methods could lead to different RNA fragmentation patterns, which could also explain the observed inconsistency between qPCR quantification and sequencing outcomes. Overall, extra attention should be paid to wastewater sample processing (i.e., concentration and homogenization) for sufficient and good quality SARS-CoV-2 RNA for downstream sequencing.

Interlaboratory performance and quantitative PCR data acceptance metrics for NIST SRM® 2917.

Surface water quality quantitative polymerase chain reaction (qPCR) technologies are expanding from a subject of research to routine environmental and public health laboratory testing. Readily available, reliable reference material is needed to interpret qPCR measurements, particularly across laboratories. Standard Reference Material® 2917 (NIST SRM® 2917) is a DNA plasmid construct that functions with multiple water quality qPCR assays allowing for estimation of total fecal pollution and identification of key fecal sources. This study investigates SRM 2917 interlaboratory performance based on repeated measures of 12 qPCR assays by 14 laboratories (n = 1008 instrument runs). Using a Bayesian approach, single-instrument run data are combined to generate assay-specific global calibration models allowing for characterization of within- and between-lab variability. Comparable data sets generated by two additional laboratories are used to assess new SRM 2917 data acceptance metrics. SRM 2917 allows for reproducible single-instrument run calibration models across laboratories, regardless of qPCR assay. In addition, global models offer multiple data acceptance metric options that future users can employ to minimize variability, improve comparability of data across laboratories, and increase confidence in qPCR measurements.

Reduction and discharge of SARS-CoV-2 RNA in Chicago-area water reclamation plants.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA is commonly excreted in the feces and urine of infected individuals and is, therefore, detected in wastewaters where infection is present in the surrounding population. Water reclamation plants (WRPs) that treat these wastewaters commonly discharge treated effluents into the surrounding environment, yet little is known about the removal or persistence of SARS-CoV-2 RNA through wastewater treatment systems and potential for eventual release into the environment. We collected 361 24-hour composite influent and effluent samples from seven WRPs in the Greater Chicago Area in Illinois. Samples were collected over a period of 21 weeks for three large WRPs (with design max flows of 1.89-2.32 billion gallons per day and serving a combined population of 4.62 million people) and 11 weeks for four smaller WRPs (with design max flows of 96.3-186 million gallons per day and serving a combined population of >0.5 million people). A total of two of the larger WRPs implemented seasonal disinfection (using UV light or chlorination/dechlorination) for 8 weeks of this sampling period. SARS-CoV-2 RNA was quantified in the influent and effluent samples by reverse-transcription quantitative PCR (RT-qPCR) of the N1 and N2 targets of the nucleocapsid (N) gene. Although SARS-CoV-2 RNA was regularly detected in influent and effluent from all WRPs, viral RNA concentrations in the effluent samples were considerably lower, with mean effluent: influent gene copy concentration ratios ranging from 1:160 to 1:2.95 between WRPs. Samples collected while disinfection was active vs. inactive did not show any significant difference in the portion of RNA persisting through the treatment process (P > .05).

Standardizing data reporting in the research community to enhance the utility of open data for SARS-CoV-2 wastewater surveillance.

SARS-CoV-2 RNA detection in wastewater is being rapidly developed and adopted as a public health monitoring tool worldwide. With wastewater surveillance programs being implemented across many different scales and by many different stakeholders, it is critical that data collected and shared are accompanied by an appropriate minimal amount of metainformation to enable meaningful interpretation and use of this new information source and intercomparison across datasets. While some databases are being developed for specific surveillance programs locally, regionally, nationally, and internationally, common globally-adopted data standards have not yet been established within the research community. Establishing such standards will require national and international consensus on what metainformation should accompany SARS-CoV-2 wastewater measurements. To establish a recommendation on minimum information to accompany reporting of SARS-CoV-2 occurrence in wastewater for the research community, the United States National Science Foundation (NSF) Research Coordination Network on Wastewater Surveillance for SARS-CoV-2 hosted a workshop in February 2021 with participants from academia, government agencies, private companies, wastewater utilities, public health laboratories, and research institutes. This report presents the primary two outcomes of the workshop: (i) a recommendation on the set of minimum meta-information that is needed to confidently interpret wastewater SARS-CoV-2 data, and (ii) insights from workshop discussions on how to improve standardization of data reporting.

Fecal pollution source characterization at non-point source impacted beaches under dry and wet weather conditions.

Though Lake Michigan beaches in Chicago are not impacted by stormwater or wastewater outfalls, several of those beaches often exceed USEPA Beach Action Values (BAVs). We investigated the role of microbial source tracking (MST) as a complement to routine beach monitoring at Chicago beaches. In summer 2016, water samples from nine Chicago beaches were analyzed for E. coli by culture and enterococci by qPCR. A total of 195 archived samples were then tested for human (HF183/BacR287, HumM2), canine (DG3, DG37), and avian (GFD) microbial source tracking (MST) markers. Associations between MST and general fecal indicator bacteria (FIB) measures were evaluated and stratified based on wet and dry weather definitions. Among the 195 samples, HF183/BacR287 was quantifiable in 4%, HumM2 in 1%, DG3 in 6%, DG37 in 2%, and GFD in 23%. The one beach with a dog area was far more likely to have DG3 present in the quantifiable range than other beaches. Exceedance of general FIB BAVs increased the odds of human, dog and avian marker detection. MST marker weighted-average fecal scores for DG3 was 2.4 times, DG37 was 2.1 times, and GFD was 1.6 times higher during wet compared to dry weather conditions. HF183/BacR287 weighted-average fecal scores were not associated with precipitation. Associations between FIB BAV exceedance and MST marker detection were generally stronger in wet weather. Incorporating MST testing into routine beach water monitoring can provide information that beach managers can use when developing protection plans for beaches not impacted by point sources.

Slow adoption of rapid testing: Beach monitoring and notification using qPCR.

In 2012 the US Environmental Protection Agency published new Recreational Water Quality Criteria, which for the first time, included criteria values and beach action values for quantitative polymerase chain reaction (qPCR) measurements or estimates of enterococci. The qPCR method makes it possible to generate indicator bacterial test results within several hours, and notify the public immediately, rather than the following day, which would be the case if culture methods were used. The BEach ACtion and Closing Online Notification (BEACON) data demonstrates that less than 1% of microbial beach water results for the years 2014-2018 were generated using qPCR. In order to assist jurisdictions considering the implementation of same-day beach water monitoring and notification, we describe a qPCR-based beach monitoring program in which a central laboratory tests water samples from up to 20 beaches per day, seven days per week, and reports the results to the public by noon. The transition from a culture-based monitoring program to a qPCR program, staffing, management, communications needs, fixed costs, and variable costs of the program are described. USEPA funding to support state and local governments implementing qPCR programs may be needed if the benefits of same-day notification regarding elevated health risks are to be realized.

Solar Powered Microplasma-Generated Ozone: Assessment of a Novel Point-of-Use Drinking Water Treatment Method.

Ozonation is widely used in high-income countries for water disinfection in centralized treatment facilities. New microplasma technology has reduced the energy requirements for ozone generation dramatically, such that a 15-watt solar panel is sufficient to produce small quantities of ozone. This technology has not been used previously for point-of-use drinking water treatment. We conducted a series of assessments of this technology, both in the laboratory and in homes of residents of a village in western Kenya, to estimate system efficacy and to determine if the solar-powered point-of-use water ozonation system appears safe and acceptable to end-users. In the laboratory, two hours of point-of-use ozonation reduced E. coli in 120 L of wastewater by a mean (standard deviation) of 2.3 (0.84) log-orders of magnitude and F+ coliphage by 1.54 (0.72). Based on laboratory efficacy, 10 families in Western Kenya used the system to treat 20 L of household stored water for two hours on a daily basis for eight weeks. Household stored water E. coli concentrations of >1000 most probable number (MPN)/100 mL were reduced by 1.56 (0.96) log removal value (LRV). No participants experienced symptoms of respiratory or mucous membrane irritation. Focus group research indicated that families who used the system for eight weeks had very favorable perceptions of the system, in part because it allowed them to charge mobile phones. Drinking water ozonation using microplasma technology may be a sustainable point-of-use treatment method, although system optimization and evaluations in other settings would be needed.

Evaluation of multiple laboratory performance and variability in analysis of recreational freshwaters by a rapid Escherichia coli qPCR method (Draft Method C).

There is interest in the application of rapid quantitative polymerase chain reaction (qPCR) methods for recreational freshwater quality monitoring of the fecal indicator bacteria Escherichia coli (E. coli). In this study we determined the performance of 21 laboratories in meeting proposed, standardized data quality acceptance (QA) criteria and the variability of target gene copy estimates from these laboratories in analyses of 18 shared surface water samples by a draft qPCR method developed by the U.S. Environmental Protection Agency (EPA) for E. coli. The participating laboratories ranged from academic and government laboratories with more extensive qPCR experience to "new" water quality and public health laboratories with relatively little previous experience in most cases. Failures to meet QA criteria for the method were observed in 24% of the total 376 test sample analyses. Of these failures, 39% came from two of the "new" laboratories. Likely factors contributing to QA failures included deviations in recommended procedures for the storage and preparation of reference and control materials. A master standard curve calibration model was also found to give lower overall variability in log10 target gene copy estimates than the delta-delta Ct (ΔΔCt) calibration model used in previous EPA qPCR methods. However, differences between the mean estimates from the two models were not significant and variability between laboratories was the greatest contributor to overall method variability in either case. Study findings demonstrate the technical feasibility of multiple laboratories implementing this or other qPCR water quality monitoring methods with similar data quality acceptance criteria but suggest that additional practice and/or assistance may be valuable, even for some more generally experienced qPCR laboratories. Special attention should be placed on providing and following explicit guidance on the preparation, storage and handling of reference and control materials.

Standardized data quality acceptance criteria for a rapid Escherichia coli qPCR method (Draft Method C) for water quality monitoring at recreational beaches.

There is growing interest in the application of rapid quantitative polymerase chain reaction (qPCR) and other PCR-based methods for recreational water quality monitoring and management programs. This interest has strengthened given the publication of U.S. Environmental Protection Agency (EPA)-validated qPCR methods for enterococci fecal indicator bacteria (FIB) and has extended to similar methods for Escherichia coli (E. coli) FIB. Implementation of qPCR-based methods in monitoring programs can be facilitated by confidence in the quality of the data produced by these methods. Data quality can be determined through the establishment of a series of specifications that should reflect good laboratory practice. Ideally, these specifications will also account for the typical variability of data coming from multiple users of the method. This study developed proposed standardized data quality acceptance criteria that were established for important calibration model parameters and/or controls from a new qPCR method for E. coli (EPA Draft Method C) based upon data that was generated by 21 laboratories. Each laboratory followed a standardized protocol utilizing the same prescribed reagents and reference and control materials. After removal of outliers, statistical modeling based on a hierarchical Bayesian method was used to establish metrics for assay standard curve slope, intercept and lower limit of quantification that included between-laboratory, replicate testing within laboratory, and random error variability. A nested analysis of variance (ANOVA) was used to establish metrics for calibrator/positive control, negative control, and replicate sample analysis data. These data acceptance criteria should help those who may evaluate the technical quality of future findings from the method, as well as those who might use the method in the future. Furthermore, these benchmarks and the approaches described for determining them may be helpful to method users seeking to establish comparable laboratory-specific criteria if changes in the reference and/or control materials must be made.

Evaluation of rapid qPCR method for quantification of E. coli at non-point source impacted Lake Michigan beaches.

Most Great Lakes communities rely on culture-based E. coli methods for monitoring fecal indicator bacteria (FIB) at recreational beaches. These cultivation methods require 18 or more hours to generate results. As a consequence, public notifications about beach action value (BAV) exceedance are based on prior-day water quality. Rapid qPCR monitoring of bacteria in beach water solves the 24-h delay problem, though the USEPA-approved qPCR method targets enterococci bacteria, while Great Lakes communities are familiar with E. coli monitoring. For an E. coli qPCR method to be useful for water quality management, it is important to systematically characterize method performance, and establish BAVs for public notification purposes. In this study, we 1) evaluated a draft USEPA E. coli qPCR method, 2) compared E. coli qPCR measurements with two established FIB (E. coli culture and enterococci qPCR) results, and explored potential strategies to establish E. coli qPCR BAV criteria in the absence of an epidemiological study. Based on analyses of 288 water samples collected from eight of Chicago's Lake Michigan beaches, the E. coli qPCR method demonstrates acceptable performance characteristics. The method is prone to low level DNA contamination, possibly originating from assay reagents derived from E. coli bacteria. Both E. coli and enterococci BAVs were exceeded in approximately 18% of the samples. E. coli qPCR values were correlated with both E. coli culture (r = 0.83; p < 0.0001) and enterococci qPCR (r = 0.67; p < 0.0001) values. The approach recommended by the USEPA in its Technical Support Material (TSM) was used to generate candidate E. coli qPCR BAVs, as was receiver operating characteristic (ROC) analysis. Potential BAV thresholds differed substantially, ranging from 200.9 calibrator cell equivalents (CCE)/100 mL (ROC analysis, enterococci qPCR BAV as the reference) to 1000 CCE/100 mL (TSM analysis, enterococci qPCR BAV as the reference). Because we found that different approaches to establishing potential BAVs generate quite different values, guidance from USEPA about approaches to defining comparable BAVs would be useful.

Monitoring urban beaches with qPCR vs. culture measures of fecal indicator bacteria: Implications for public notification.

BACKGROUND: The United States Environmental Protection Agency has established methods for testing beach water using the rapid quantitative polymerase chain reaction (qPCR) method, as well as "beach action values" so that the results of such testing can be used to make same-day beach management decisions. Despite its numerous advantages over culture-based monitoring approaches, qPCR monitoring has yet to become widely used in the US or elsewhere. Considering qPCR results obtained on a given day as the best available measure of that day's water quality, we evaluated the frequency of correct vs. incorrect beach management decisions that are driven by culture testing. METHODS: Beaches in Chicago, USA, were monitored using E. coli culture and enterococci qPCR methods over 894 beach-days in the summers of 2015 and 2016. Agreement in beach management using the two methods, after taking into account agreement due to chance, was summarized using Cohen's kappa statistic. RESULTS: No meaningful agreement (beyond that expected by chance) was observed between beach management actions driven by the two pieces of information available to beach managers on a given day: enterococci qPCR results ofsamples collected that morning and E. coli culture results of samples collected the previous day. The E. coli culture beach action value was exceeded 3.4 times more frequently than the enterococci qPCR beach action value (22.6 vs. 6.6% of beach-days). CONCLUSIONS: The largest evaluation of qPCR-based beach monitoring to date provides little scientific rationale for continued E. coli culture testing of beach water in our setting. The observation that the E. coli culture beach action value was exceeded three times as frequently as the enterococci qPCR beach action value suggests that, although the beach action values for bacteria using different measurement methods are thought to provide comparable information about health risk, this does not appear to be the case in all settings.