Respiratory virus concentrations in human excretions that contribute to wastewater: a systematic review and meta-analysis.

Concentrations of nucleic acids from a range of respiratory viruses in wastewater solids collected from wastewater treatment plants correlate to clinical data on disease occurrence in the community contributing to the wastewater. Viral nucleic acids enter wastewater from excretions deposited in toilets or drains. To relate measured concentrations in wastewater at a treatment plant to the number of community infections, viral nucleic-acid concentrations in human excretions are needed as inputs to a mass balance model. Here, we carried out a systematic review and meta-analysis to characterize the concentrations and presence of influenza A and B, respiratory syncytial virus, metapneumovirus, parainfluenza virus, rhinovirus, and seasonal coronaviruses in stool, urine, mucus, sputum, and saliva. We identified 220 data sets from 50 articles and reported viral concentrations and presence in these excretions. Data were unevenly distributed across virus type (with the most available for influenza) and excretion type (with the most available for respiratory excretions). Most articles only reported the presence or absence of the virus in a cross-sectional study design. There is a need for more concentration data, including longitudinal data, across all respiratory virus and excretion types. Such data would allow quantitatively linking virus wastewater concentrations to numbers of infected individuals.

Wastewater concentrations of human influenza, metapneumovirus, parainfluenza, respiratory syncytial virus, rhinovirus, and seasonal coronavirus nucleic-acids during the COVID-19 pandemic: a surveillance study.

BACKGROUND: Respiratory disease is a major cause of morbidity and mortality; however, surveillance for circulating respiratory viruses is passive and biased. Wastewater-based epidemiology has been used to understand SARS-CoV-2, influenza A, and respiratory syncytial virus (RSV) infection rates at a community level but has not been used to investigate other respiratory viruses. We aimed to use wastewater-based epidemiology to understand community viral respiratory infection occurrence. METHODS: A retrospective wastewater-based epidemiology surveillance study was carried out at a large wastewater treatment plant located in California, USA. Using droplet digital RT-PCR, we measured RNA concentrations of influenza A and influenza B viruses, RSV A and RSV B, parainfluenza (1-4) viruses, rhinovirus, seasonal coronaviruses, and metapneumovirus in wastewater solids three times per week for 17 months (216 samples) between Feb 1, 2021, and June 21, 2022. Novel probe-based RT-PCR assays for non-influenza viral targets were developed and validated. We compared viral RNA concentrations to positivity rates for viral infections from clinical specimens submitted to California Sentinel Clinical Laboratories (sentinel laboratories) to assess concordance between the two datasets. FINDINGS: We detected RNA from all tested viruses in wastewater solids. Human rhinovirus (median concentration 4300 [0-9500] copies per gram dry weight) and seasonal human coronaviruses (35 000 [17 000-56 000]) were found at the highest concentrations. Concentrations of viral RNA correlated significantly and positively with positivity rates of associated viral diseases from sentinel laboratories (tau 0·32-0·57, p<0·0009); the only exceptions were influenza B and RSV A, which were rarely detected in wastewater solids. Measurements from wastewater indicated coronavirus OC43 dominated the seasonal human coronavirus infections whereas parainfluenza 3 dominated among parainfluenza infections during the study period. Concentrations of all tested viral RNA decreased noticeably after the omicron BA.1 surge suggesting a connection between changes in human behaviour during the surge and transmission of all respiratory viruses. INTERPRETATION: Wastewater-based epidemiology can be used to obtain information on circulation of respiratory viruses at a localised, community level without the need to test many individuals because a single sample of wastewater represents the entire contributing community. Results from wastewater can be available within 24 h of sample collection, generating real time information to inform public health responses, clinical decision making, and individual behaviour modifications. FUNDING: CDC Foundation.

Effect of SARS-CoV-2 digital droplet RT-PCR assay sensitivity on COVID-19 wastewater based epidemiology

We developed and implemented a framework for examining how molecular assay sensitivity for a viral RNA genome target affects its utility for wastewater-based epidemiology. We applied this framework to digital droplet RT-PCR measurements of SARS-CoV-2 and Pepper Mild Mottle Virus genes in wastewater. Measurements were made using 10 replicate wells which allowed for high assay sensitivity, and therefore enabled detection of SARS-CoV-2 RNA even when COVID-19 incidence rates were relatively low (~10−5). We then used a computational downsampling approach to determine how using fewer replicate wells to measure the wastewater concentration reduced assay sensitivity and how the resultant reduction affected the ability to detect SARS-CoV-2 RNA at various COVID-19 incidence rates. When percent of positive droplets was between 0.024% and 0.5% (as was the case for SARS-CoV-2 genes during the Delta surge), measurements obtained with 3 or more wells were similar to those obtained using 10. When percent of positive droplets was less than 0.024% (as was the case prior to the Delta surge), then 6 or more wells were needed to obtain similar results as those obtained using 10 wells. When COVID-19 incidence rate is low (~ 10−5), as it was before the Delta surge and SARS-CoV-2 gene concentrations are <104 cp/g, using 6 wells will yield a detectable concentration 90% of the time. Overall, results support an adaptive approach where assay sensitivity is increased by running 6 or more wells during periods of low SARS-CoV-2 gene concentrations, and 3 or more wells during periods of high SARS-CoV-2 gene concentrations.

Looking Forward: The Role of Academic Researchers in Building Sustainable Wastewater Surveillance Programs.

BACKGROUND: In just over 2 years, tracking the COVID-19 pandemic through wastewater surveillance advanced from early reports of successful SARS-CoV-2 RNA detection in untreated wastewater to implementation of programs in at least 60 countries. Early wastewater monitoring efforts primarily originated in research laboratories and are now transitioning into more formal surveillance programs run in commercial and public health laboratories. A major challenge in this progression has been to simultaneously optimize methods and build scientific consensus while implementing surveillance programs, particularly during the rapidly changing landscape of the pandemic. Translating wastewater surveillance results for effective use by public health agencies also remains a key objective for the field. OBJECTIVES: We examined the evolution of wastewater surveillance to identify model collaborations and effective partnerships that have created rapid and sustained success. We propose needed areas of research and key roles academic researchers can play in the framework of wastewater surveillance to aid in the transition from early monitoring efforts to more formalized programs within the public health system. DISCUSSION: Although wastewater surveillance has rapidly developed as a useful public health tool for tracking COVID-19, there remain technical challenges and open scientific questions that academic researchers are equipped to address. This includes validating methodology and backfilling important knowledge gaps, such as fate and transport of surveillance targets and epidemiological links to wastewater concentrations. Our experience in initiating and implementing wastewater surveillance programs in the United States has allowed us to reflect on key barriers and draw useful lessons on how to promote synergy between different areas of expertise. As wastewater surveillance programs are formalized, the working relationships developed between academic researchers, commercial and public health laboratories, and data users should promote knowledge co-development. We believe active involvement of academic researchers will contribute to building robust surveillance programs that will ultimately provide new insights into population health. https://doi.org/10.1289/EHP11519.

When case reporting becomes untenable: Can sewer networks tell us where COVID-19 transmission occurs?

Monitoring SARS-CoV-2 in wastewater is a valuable approach to track COVID-19 transmission. Designing wastewater surveillance (WWS) with representative sampling sites and quantifiable results requires knowledge of the sewerage system and virus fate and transport. We developed a multi-level WWS system to track COVID-19 in Atlanta using an adaptive nested sampling strategy. From March 2021 to April 2022, 868 wastewater samples were collected from influent lines to wastewater treatment facilities and upstream community manholes. Variations in SARS-CoV-2 concentrations in influent line samples preceded similar variations in numbers of reported COVID-19 cases in the corresponding catchment areas. Community sites under nested sampling represented mutually-exclusive catchment areas. Community sites with high SARS-CoV-2 detection rates in wastewater covered high COVID-19 incidence areas, and adaptive sampling enabled identification and tracing of COVID-19 hotspots. This study demonstrates how a well-designed WWS provides actionable information including early warning of surges in cases and identification of disease hotspots.

Regional Replacement of SARS-CoV-2 Variant Omicron BA.1 with BA.2 as Observed through Wastewater Surveillance.

Greater knowledge of circulating SARS-CoV-2 variants can inform pandemic response, vaccine development, disease epidemiology, and use of monoclonal antibody treatments. We developed custom assays targeting characteristic mutations in SARS-CoV-2 variants Omicron BA.1 and BA.2 and confirmed their sensitivity and specificity in silico and in vitro. We then applied these assays to daily wastewater solid samples from eight publicly owned treatment works in the greater Bay Area of California, United States, over four months to obtain a spatially and temporally intensive data set. We documented regional replacement of BA.1 with BA.2 in agreement with, and ahead of, clinical sequencing data. This study highlights the utility of wastewater surveillance for real-time tracking of SARS-CoV-2 sublineage circulation. The results suggest that concerted efforts to design RT-PCR assays that target variant and variant sublineage characteristic mutations for wide-scale wastewater monitoring implementation will be informative for pandemic response.

Wastewater-Based Estimation of the Effective Reproductive Number of SARS-CoV-2.

BACKGROUND: The effective reproductive number, Re, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, Re estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. These estimates are temporarily biased when clinical testing or reporting strategies change. OBJECTIVES: We show that the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater can be used to estimate Re in near real time, independent of clinical data and without the associated biases. METHODS: We collected longitudinal measurements of SARS-CoV-2 RNA in wastewater in Zurich, Switzerland, and San Jose, California, USA. We combined this data with information on the temporal dynamics of shedding (the shedding load distribution) to estimate a time series proportional to the daily COVID-19 infection incidence. We estimated a wastewater-based Re from this incidence. RESULTS: The method to estimate Re from wastewater worked robustly on data from two different countries and two wastewater matrices. The resulting estimates were as similar to the Re estimates from case report data as Re estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer Re. DISCUSSION: To our knowledge, this is the first time Re has been estimated from wastewater. This method provides a low-cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens. https://doi.org/10.1289/EHP10050.

SARS-CoV-2 RNA Wastewater Settled Solids Surveillance Frequency and Impact on Predicted COVID-19 Incidence Using a Distributed Lag Model

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater settled solids correlate well with coronavirus disease 2019 (COVID-19) incidence rates (IRs). Here, we develop distributed lag models to estimate IRs using concentrations of SARS-CoV-2 RNA from wastewater solids and investigate the impact of sampling frequency on model performance. SARS-CoV-2 N gene and pepper mild mottle virus (PMMoV) RNA concentrations were measured daily at four wastewater treatment plants in California. Artificially reduced data sets were produced for each plant with sampling frequencies of once every 2, 3, 4, and 7 days. Sewershed-specific models that related daily N/PMMoV to IR were fit for each sampling frequency with data from mid-November 2020 through mid-July 2021, which included the period of time during which Delta emerged. Models were used to predict IRs during a subsequent out-of-sample time period. When sampling occurred at least once every 4 days, the in- and out-of-sample root-mean-square error changed by <7 cases/100 000 compared to daily sampling across sewersheds. This work illustrates that real-time, daily predictions of IR are possible with small errors, despite changes in circulating variants, when sampling frequency is once every 4 days or more. However, reduced sampling frequency may not serve other important wastewater surveillance use cases. Distributed lag models predicted COVID-19 incidence rates with relatively small errors using wastewater solids surveillance of SARS-CoV-2 N genes.

Estimating Relative Abundance of 2 SARS-CoV-2 Variants through Wastewater Surveillance at 2 Large Metropolitan Sites, United States.

Monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) is critical for public health management of coronavirus disease. Sequencing is resource-intensive and incompletely representative, and not all isolates can be sequenced. Because wastewater SARS-CoV-2 RNA concentrations correlate with coronavirus disease incidence in sewersheds, tracking VOCs through wastewater is appealing. We developed digital reverse transcription PCRs to monitor abundance of select mutations in Alpha and Delta VOCs in wastewater settled solids, applied these to July 2020-August 2021 samples from 2 large US metropolitan sewersheds, and compared results to estimates of VOC abundance from case isolate sequencing. Wastewater measurements tracked closely with case isolate estimates (Alpha, rp 0.82-0.88; Delta, rp 0.97). Mutations were detected in wastewater even at levels <5% of total SARS-CoV-2 RNA and in samples available 1-3 weeks before case isolate results. Wastewater variant monitoring should be strategically deployed to complement case isolate sequencing.

Detection of SARS-CoV-2 Variants Mu, Beta, Gamma, Lambda, Delta, Alpha, and Omicron in Wastewater Settled Solids Using Mutation-Specific Assays Is Associated with Regional Detection of Variants in Clinical Samples.

Changes in the circulation of SARS-CoV-2 variants of concern (VOCs) may require changes in the public health response to the COVID-19 pandemic, as they have the potential to evade vaccines and pharmaceutical interventions and may be more transmissive than other SARS-CoV-2 variants. As such, it is essential to track and prevent their spread in susceptible communities. We developed digital reverse transcription (RT)-PCR assays for mutations characteristic of VOCs and used them to quantify those mutations in samples of wastewater settled solids collected from a publicly owned treatment works (POTW) during different phases of the COVID-19 pandemic. Wastewater concentrations of single mutations characteristic of each VOC, normalized by the concentration of a conserved SARS-CoV-2 N gene, correlate with regional estimates of the proportion of clinical infections caused by each VOC. These results suggest that targeted RT-PCR assays can be used to detect variants circulating in communities and inform the public health response to the pandemic. IMPORTANCE Wastewater represents a pooled biological sample of the contributing community and thus a resource for assessing community health. Here, we show that emergence, spread, and disappearance of SARS-CoV-2 infections caused by variants of concern are reflected in the presence of variant genomic RNA in wastewater settled solids. This work highlights an important public health use case for wastewater.

SARS-CoV-2 RNA is enriched by orders of magnitude in primary settled solids relative to liquid wastewater at publicly owned treatment works.

Wastewater-based epidemiology has gained attention throughout the world for detection of SARS-CoV-2 RNA in wastewater to supplement clinical testing. Raw wastewater consists of small particles, or solids, suspended in liquid. Methods have been developed to measure SARS-CoV-2 RNA in the liquid and the solid fraction of wastewater, with some studies reporting higher concentrations in the solid fraction. To investigate this relationship further, six laboratories collaborated to conduct a study across five publicly owned treatment works (POTWs) where both primary settled solids obtained from primary clarifiers and raw wastewater influent samples were collected and quantified for SARS-CoV-2 RNA. Settled solids and influent samples were processed by participating laboratories using their respective methods and retrospectively paired based on date of collection. SARS-CoV-2 RNA concentrations, on a mass equivalent basis, were higher in settled solids than in influent by approximately three orders of magnitude. Concentrations in matched settled solids and influent were positively and significantly correlated at all five POTWs. RNA concentrations in both settled solids and influent were correlated to COVID-19 incidence rates in the sewersheds and thus representative of disease occurrence; the settled solids methods appeared to produce a comparable relationship between SARS-CoV-2 RNA concentration measurements and incidence rates across all POTWs. Settled solids and influent methods showed comparable sensitivity, N gene detection frequency, and calculated empirical incidence rate lower limits. Analysis of settled solids for SARS-CoV-2 RNA has the advantage of using less sample volume to achieve similar sensitivity to influent methods.

High-Frequency, High-Throughput Quantification of SARS-CoV-2 RNA in Wastewater Settled Solids at Eight Publicly Owned Treatment Works in Northern California Shows Strong Association with COVID-19 Incidence.

A number of recent retrospective studies have demonstrated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater are associated with coronavirus disease 2019 (COVID-19) cases in the corresponding sewersheds. Implementing high-resolution, prospective efforts across multiple plants depends on sensitive measurements that are representative of COVID-19 cases, scalable for high-throughput analysis, and comparable across laboratories. We conducted a prospective study across eight publicly owned treatment works (POTWs). A focus on SARS-CoV-2 RNA in solids enabled us to scale up our measurements with a commercial lab partner. Samples were collected daily, and results were posted to a website within 24 h. SARS-CoV-2 RNA in daily samples correlated with the incidence of COVID-19 cases in the sewersheds; a 1 log10 increase in SARS-CoV-2 RNA in settled solids corresponds to a 0.58 log10 (4×) increase in sewershed incidence rate. SARS-CoV-2 RNA signals measured with the commercial laboratory partner were comparable across plants and comparable to measurements conducted in a university laboratory when normalized by pepper mild mottle virus (PMMoV) RNA. Results suggest that SARS-CoV-2 RNA should be detectable in settled solids for COVID-19 incidence rates of >1/100,000 (range, 0.8 to 2.3 cases per 100,000). These sensitive, representative, scalable, and comparable methods will be valuable for future efforts to scale up wastewater-based epidemiology. IMPORTANCE Access to reliable, rapid monitoring data is critical to guide response to an infectious disease outbreak. For pathogens that are shed in feces or urine, monitoring wastewater can provide a cost-effective snapshot of transmission in an entire community via a single sample. In order for a method to be useful for ongoing COVID-19 monitoring, it should be sensitive for detection of low concentrations of SARS-CoV-2, representative of incidence rates in the community, scalable to generate data quickly, and comparable across laboratories. This paper presents a method utilizing wastewater solids to meet these goals, producing measurements of SARS-CoV-2 RNA strongly associated with COVID-19 cases in the sewershed of a publicly owned treatment work. Results, provided within 24 h, can be used to detect incidence rates as low as approximately 1/100,000 cases and can be normalized for comparison across locations generating data using different methods.

Standardized preservation, extraction and quantification techniques for detection of fecal SARS-CoV-2 RNA.

Patients with COVID-19 shed SARS-CoV-2 RNA in stool, sometimes well after their respiratory infection has cleared. This may be significant for patient health, epidemiology, and diagnosis. However, methods to preserve stool, and to extract and quantify viral RNA are not standardized. We test the performance of three preservative approaches at yielding detectable SARS-CoV-2 RNA: the OMNIgene-GUT kit, Zymo DNA/RNA shield kit, and the most commonly applied, storage without preservative. We test these in combination with three extraction kits: QIAamp Viral RNA Mini Kit, Zymo Quick-RNA Viral Kit, and MagMAX Viral/Pathogen Kit. We also test the utility of ddPCR and RT-qPCR for the reliable quantification of SARS-CoV-2 RNA from stool. We identify that the Zymo DNA/RNA preservative and the QiaAMP extraction kit yield more detectable RNA than the others, using both ddPCR and RT-qPCR. Taken together, we recommend a comprehensive methodology for preservation, extraction and detection of RNA from SARS-CoV-2 and other coronaviruses in stool.

Effect of storage conditions on SARS-CoV-2 RNA quantification in wastewater solids.

SARS-CoV-2 RNA in wastewater settled solids is associated with COVID-19 incidence in sewersheds and therefore, there is a strong interest in using these measurements to augment traditional disease surveillance methods. A wastewater surveillance program should provide rapid turn around for sample measurements (ideally within 24 hours), but storage of samples is necessary for a variety of reasons including biobanking. Here we investigate how storage of wastewater solids at 4 °C, -20 °C, and -80 °C affects measured concentrations of SARS-CoV-2 RNA. We find that short term (7 or 8 d) storage of raw solids at 4 °C has little effect on measured concentrations of SARS-CoV-2 RNA, whereas longer term storage at 4 °C (35-122 d) or freezing reduces measurements by 60%, on average. We show that normalizing SARS-CoV-2 RNA concentrations by concentrations of pepper mild mottle virus (PMMoV) RNA, an endogenous wastewater virus, can correct for changes during storage as storage can have a similar effect on PMMoV RNA as on SARS-CoV-2 RNA. The reductions in SARS-CoV-2 RNA in solids during freeze thaws is less than those reported for the same target in liquid influent by several authors.

SARS-CoV-2 RNA in Wastewater Settled Solids Is Associated with COVID-19 Cases in a Large Urban Sewershed.

Wastewater-based epidemiology may be useful for informing public health response to viral diseases like COVID-19 caused by SARS-CoV-2. We quantified SARS-CoV-2 RNA in wastewater influent and primary settled solids in two wastewater treatment plants to inform the preanalytical and analytical approaches and to assess whether influent or solids harbored more viral targets. The primary settled solids samples resulted in higher SARS-CoV-2 detection frequencies than the corresponding influent samples. Likewise, SARS-CoV-2 RNA was more readily detected in solids using one-step digital droplet (dd)RT-PCR than with two-step RT-QPCR and two-step ddRT-PCR, likely owing to reduced inhibition with the one-step ddRT-PCR assay. We subsequently analyzed a longitudinal time series of 89 settled solids samples from a single plant for SARS-CoV-2 RNA as well as coronavirus recovery (bovine coronavirus) and fecal strength (pepper mild mottle virus) controls. SARS-CoV-2 RNA targets N1 and N2 concentrations correlated positively and significantly with COVID-19 clinically confirmed case counts in the sewershed. Together, the results demonstrate that measuring SARS-CoV-2 RNA concentrations in settled solids may be a more sensitive approach than measuring SARS-CoV-2 in influent.