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.

Trends of Enterovirus D68 Concentrations in Wastewater, California, USA, February 2021-April 2023.

In this retrospective study, we measured enterovirus D68 (EV-D68) genomic RNA in wastewater solids longitudinally at 2 California, USA, wastewater treatment plants twice per week for 26 months. EV-D68 RNA was undetectable except when concentrations increased from mid-July to mid-December 2022, which coincided with a peak in confirmed EV-D68 cases.

The Tomato Brown Rugose Fruit Virus Movement Protein Gene Is a Novel Microbial Source Tracking Marker.

Microbial source tracking (MST) identifies sources of fecal contamination in the environment using host-associated fecal markers. While there are numerous bacterial MST markers that can be used herein, there are few such viral markers. Here, we designed and tested novel viral MST markers based on tomato brown rugose fruit virus (ToBRFV) genomes. We assembled eight nearly complete genomes of ToBRFV from wastewater and stool samples from the San Francisco Bay Area in the United States. Next, we developed two novel probe-based reverse transcription-PCR (RT-PCR) assays based on conserved regions of the ToBRFV genome and tested the markers' sensitivities and specificities using human and non-human animal stool as well as wastewater. The ToBRFV markers are sensitive and specific; in human stool and wastewater, they are more prevalent and abundant than a commonly used viral marker, the pepper mild mottle virus (PMMoV) coat protein (CP) gene. We used the assays to detect fecal contamination in urban stormwater samples and found that the ToBRFV markers matched cross-assembly phage (crAssphage), an established viral MST marker, in prevalence across samples. Taken together, these results indicate that ToBRFV is a promising viral human-associated MST marker. IMPORTANCE Human exposure to fecal contamination in the environment can cause transmission of infectious diseases. Microbial source tracking (MST) can identify sources of fecal contamination so that contamination can be remediated and human exposures can be reduced. MST requires the use of host-associated MST markers. Here, we designed and tested novel MST markers from genomes of tomato brown rugose fruit virus (ToBRFV). The markers are sensitive and specific to human stool and highly abundant in human stool and wastewater samples.

Adsorption of Respiratory Syncytial Virus, Rhinovirus, SARS-CoV-2, and F+ Bacteriophage MS2 RNA onto Wastewater Solids from Raw Wastewater.

Despite the widespread adoption of wastewater surveillance, more research is needed to understand the fate and transport of viral genetic markers in wastewater. This information is essential for optimizing monitoring strategies and interpreting wastewater surveillance data. In this study, we examined the solid-liquid partitioning behavior of four viruses in wastewater: SARS-CoV-2, respiratory syncytial virus (RSV), rhinovirus (RV), and F+ coliphage/MS2. We used two approaches: (1) laboratory partitioning experiments using lab-grown viruses and (2) distribution experiments using endogenous viruses in raw wastewater. Partition experiments were conducted at 4 and 22 °C. Wastewater samples were spiked with varying concentrations of each virus, solids and liquids were separated via centrifugation, and viral RNA concentrations were quantified using reverse-transcription-digital droplet PCR (RT-ddPCR). For the distribution experiments, wastewater samples were collected from six wastewater treatment plants and processed without spiking exogenous viruses; viral RNA concentrations were measured in wastewater solids and liquids. In both experiments, RNA concentrations were higher in the solid fraction than the liquid fraction by approximately 3-4 orders of magnitude. Partition coefficients (KF) ranged from 2000-270,000 mL·g-1 across viruses and temperature conditions. Distribution coefficients (Kd) were consistent with results from partitioning experiments. Further research is needed to understand how virus and wastewater characteristics might influence the partitioning of viral genetic markers in wastewater.

Sunlight Inactivation of Enveloped Viruses in Clear Water.

Enveloped virus fate in the environment is not well understood; there are no quantitative data on sunlight inactivation of enveloped viruses in water. Herein, we measured the sunlight inactivation of two enveloped viruses (Phi6 and murine hepatitis virus, MHV) and a nonenveloped virus (MS2) over time in clear water with simulated sunlight exposure. We attenuated UV sunlight wavelengths using long-pass 50% cutoff filters at 280, 305, and 320 nm. With the lowest UV attenuation tested, all decay rate constants (corrected for UV light screening, k̂) were significantly different from dark controls; the MS2 k̂ was equal to 4.5 m2/MJ, compared to 16 m2/MJ for Phi6 and 52 m2/MJ for MHV. With the highest UV attenuation tested, only k̂ for MHV (6.1 m2/MJ) was different from the dark control. Results indicate that the two enveloped viruses decay faster than the nonenveloped virus studied, and k̂ are significantly impacted by UV attenuation. Differences in k̂ may be due to the presence of viral envelopes but may also be related to other differing intrinsic properties of the viruses, including genome length and composition. Reported k̂ values can inform strategies to reduce the risk from exposure to enveloped viruses in the environment.

United States Influenza 2022-2023 Season Characteristics as Inferred from Wastewater Solids, Influenza Hospitalization, and Syndromic Data.

Influenza A virus (IAV) causes significant morbidity and mortality in the United States and has pandemic potential. Identifying IAV epidemic patterns is essential to inform the timing of vaccinations and nonpharmaceutical interventions. In a prospective, longitudinal study design, we measured IAV RNA in wastewater settled solids at 163 wastewater treatment plants across 33 states to characterize the 2022-2023 influenza season at the state, health and human services (HHS) regional, and national scales. Influenza season onset, offset, duration, peak, and intensity using IAV RNA in wastewater were compared with those determined using laboratory-confirmed influenza hospitalization rates and outpatient visits for influenza-like illness (ILI). The onset for HHS regions as determined by IAV RNA in wastewater roughly corresponded with those determined using ILI when the annual geometric mean of IAV RNA concentration was used as a baseline (i.e., the threshold that triggers onset), although offsets between the two differed. IAV RNA in wastewater provided early warning of onset, compared to the ILI estimate, when the baseline was set at twice the limit of IAV RNA detection in wastewater. Peak when determined by IAV RNA in wastewater generally preceded peak determined by IAV hospitalization rate by 2 weeks or less. IAV RNA in wastewater settled solids is an IAV-specific indicator that can be used to augment clinical surveillance for seasonal influenza epidemic timing and intensity.

Persistence of Human Norovirus (GII) in Surface Water: Decay Rate Constants and Inactivation Mechanisms.

Human norovirus (HuNoV) is an important cause of acute gastroenteritis and can be transmitted by water exposures, but its persistence in water is not well understood. Loss of HuNoV infectivity in surface water was compared with persistence of intact HuNoV capsids and genome segments. Surface water from a freshwater creek was filter-sterilized, inoculated with HuNoV (GII.4) purified from stool, and incubated at 15 or 20 °C. We measured HuNoV infectivity via the human intestinal enteroid system and HuNoV persistence via reverse transcription-quantitative polymerase chain reaction assays without (genome segment persistence) or with (intact viral capsid persistence) enzymatic pretreatment to digest naked RNA. For infectious HuNoV, results ranged from no significant decay to a decay rate constant ("k") of 2.2 day-1. In one creek water sample, genome damage was likely a dominant inactivation mechanism. In other samples from the same creek, loss of HuNoV infectivity could not be attributed to genome damage or capsid cleavage. The range in k and the difference in the inactivation mechanism observed in water from the same site could not be explained, but variable constituents in the environmental matrix could have contributed. Thus, a single k may be insufficient for modeling virus inactivation in surface waters.

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.

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.

Differential Overlap in Human and Animal Fecal Microbiomes and Resistomes in Rural versus Urban Bangladesh.

Low- and middle-income countries (LMICs) bear the largest mortality burden of antibiotic-resistant infections. Small-scale animal production and free-roaming domestic animals are common in many LMICs, yet data on zoonotic exchange of gut bacteria and antibiotic resistance genes (ARGs) in low-income communities are sparse. Differences between rural and urban communities with regard to population density, antibiotic use, and cohabitation with animals likely influence the frequency of transmission of gut bacterial communities and ARGs between humans and animals. Here, we determined the similarity in gut microbiomes, using 16S rRNA gene amplicon sequencing, and resistomes, using long-read metagenomics, between humans, chickens, and goats in a rural community compared to an urban community in Bangladesh. Gut microbiomes were more similar between humans and chickens in the rural (where cohabitation is more common) than the urban community, but there was no difference for humans and goats in the rural versus the urban community. Human and goat resistomes were more similar in the urban community, and ARG abundance was higher in urban animals than rural animals. We identified substantial overlap of ARG alleles in humans and animals in both settings. Humans and chickens had more overlapping ARG alleles than humans and goats. All fecal hosts from the urban community and rural humans carried ARGs on chromosomal contigs classified as potentially pathogenic bacteria, including Escherichia coli, Campylobacter jejuni, Clostridioides difficile, and Klebsiella pneumoniae. These findings provide insight into the breadth of ARGs circulating within human and animal populations in a rural compared to urban community in Bangladesh. IMPORTANCE While the development of antibiotic resistance in animal gut microbiomes and subsequent transmission to humans has been demonstrated in intensive farming environments and high-income countries, evidence of zoonotic exchange of antibiotic resistance in LMIC communities is lacking. This research provides genomic evidence of overlap of antibiotic resistance genes between humans and animals, especially in urban communities, and highlights chickens as important reservoirs of antibiotic resistance. Chicken and human gut microbiomes were more similar in rural Bangladesh, where cohabitation is more common. Incorporation of long-read metagenomics enabled characterization of bacterial hosts of resistance genes, which has not been possible in previous culture-independent studies using only short-read sequencing. These findings highlight the importance of developing strategies for combatting antibiotic resistance that account for chickens being reservoirs of ARGs in community environments, especially in urban areas.

Know Before You Go: Data-Driven Beach Water Quality Forecasting.

Forecasting environmental hazards is critical in preventing or building resilience to their impacts on human communities and ecosystems. Environmental data science is an emerging field that can be harnessed for forecasting, yet more work is needed to develop methodologies that can leverage increasingly large and complex data sets for decision support. Here, we design a data-driven framework that can, for the first time, forecast bacterial standard exceedances at marine beaches with 3 days lead time. Using historical data sets collected at two California sites, we train nearly 400 forecast models using statistical and machine learning techniques and test forecasts against predictions from both a naive "persistence" model and a baseline nowcast model. Overall, forecast models are found to have similar sensitivities and specificities to the persistence model, but significantly higher areas under the ROC curve (a metric distinguishing a model's ability to effectively parse classes across decision thresholds), suggesting that forecasts can provide enhanced information beyond past observations alone. Forecast model performance at all lead times was similar to that of nowcast models. Together, results suggest that integrating the forecasting framework developed in this study into beach management programs can enable better public notification and aid in proactive pollution and health risk management.

SARS-CoV-2 Wastewater Surveillance for Public Health Action.

Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has garnered extensive public attention during the coronavirus disease pandemic as a proposed complement to existing disease surveillance systems. Over the past year, methods for detection and quantification of SARS-CoV-2 viral RNA in untreated sewage have advanced, and concentrations in wastewater have been shown to correlate with trends in reported cases. Despite the promise of wastewater surveillance, for these measurements to translate into useful public health tools, bridging the communication and knowledge gaps between researchers and public health responders is needed. We describe the key uses, barriers, and applicability of SARS-CoV-2 wastewater surveillance for supporting public health decisions and actions, including establishing ethics consideration for monitoring. Although wastewater surveillance to assess community infections is not a new idea, the coronavirus disease pandemic might be the initiating event to make this emerging public health tool a sustainable nationwide surveillance system, provided that these barriers are addressed.

Transfer Rate of Enveloped and Nonenveloped Viruses between Fingerpads and Surfaces.

Fomites can represent a reservoir for pathogens, which may be subsequently transferred from surfaces to skin. In this study, we aim to understand how different factors (including virus type, surface type, time since last hand wash, and direction of transfer) affect virus transfer rates, defined as the fraction of virus transferred, between fingerpads and fomites. To determine this, 360 transfer events were performed with 20 volunteers using Phi6 (a surrogate for enveloped viruses), MS2 (a surrogate for nonenveloped viruses), and three clean surfaces (stainless steel, painted wood, and plastic). Considering all transfer events (all surfaces and both transfer directions combined), the mean transfer rates of Phi6 and MS2 were 0.17 and 0.26, respectively. Transfer of MS2 was significantly higher than that of Phi6 (P < 0.05). Surface type was a significant factor that affected the transfer rate of Phi6: Phi6 is more easily transferred to and from stainless steel and plastic than to and from painted wood. Direction of transfer was a significant factor affecting MS2 transfer rates: MS2 is more easily transferred from surfaces to fingerpads than from fingerpads to surfaces. Data from these virus transfer events, and subsequent transfer rate distributions, provide information that can be used to refine quantitative microbial risk assessments. This study provides a large-scale data set of transfer events with a surrogate for enveloped viruses, which extends the reach of the study to the role of fomites in the transmission of human enveloped viruses like influenza and SARS-CoV-2. IMPORTANCE This study created a large-scale data set for the transfer of enveloped viruses between skin and surfaces. The data set produced by this study provides information on modeling the distribution of enveloped and nonenveloped virus transfer rates, which can aid in the implementation of risk assessment models in the future. Additionally, enveloped and nonenveloped viruses were applied to experimental surfaces in an equivalent matrix to avoid matrix effects, so results between different viral species can be directly compared without confounding effects of different matrices. Our results indicating how virus type, surface type, time since last hand wash, and direction of transfer affect virus transfer rates can be used in decision-making processes to lower the risk of viral infection from transmission through fomites.

A Day at the Beach: Enabling Coastal Water Quality Prediction with High-Frequency Sampling and Data-Driven Models.

To reduce the incidence of recreational waterborne illness, fecal indicator bacteria (FIB) are measured to assess water quality and inform beach management. Recently, predictive FIB models have been used to aid managers in making beach posting and closure decisions. However, those predictive models must be trained using rich historical data sets consisting of FIB and environmental data that span years, and many beaches lack such data sets. Here, we investigate whether water quality data collected during discrete short duration, high-frequency beach sampling events (e.g., samples collected at sub-hourly intervals for 24-48 h) are sufficient to train predictive models that can be used for beach management. We use data collected during six high-frequency sampling events at three California marine beaches and train a total of 126 models using common data-driven techniques. Tide, solar irradiation, water temperature, significant wave height, and offshore wind speed were found to be the most important environmental variables in the models. We validate the predictive performance of models using withheld data. Random forests are consistently the top performing model type. Overall, we find that data-driven models trained using high-frequency FIB and environmental data perform well at predicting water quality and can be used to inform public health decisions at beaches.

Systematic Review and Meta-Analysis of the Persistence of Enveloped Viruses in Environmental Waters and Wastewater in the Absence of Disinfectants.

Enveloped viruses are characterized by a lipid-containing envelope that encapsulates the virion, and they have been the cause of major outbreaks and pandemics. Some enveloped viruses are excreted in feces and other bodily fluids of infected people and animals, raising the question of their fate in the aquatic environment. Consequently, we conducted a systematic review and meta-analysis of the decay rate constants (k) of enveloped viruses from 12 families (i.e., Coronaviridae, Cystoviridae (specifically Phi6), Filoviridae, Hepadnaviridae, Herpesviridae, Orthomyxoviridae, Paramyxoviridae, Pneumoviridae, Poxviridae, Retroviridae, Rhabdoviridae, Togaviridae) in environmental waters and wastewater to evaluate their decay kinetics and identify the environmental and virus characteristics that influence k. A total of 812 k that met inclusion criteria were identified in the literature, with the number of k for each family ranging from 0 to 560, and the virus family averaged values of k ranging from 0.11 d-1 and 1.85 d-1. Virus type (i.e., genus, species, subspecies, or subtype), method of virus enumeration (i.e., culture-based or (RT-)QPCR), and experimental water matrix type, temperature and sterility were found to have significant effects on k. Additionally, enveloped viruses were found to have statistically significantly greater k than nonenveloped viruses. Multiple linear regression models that allow prediction of log10k as a function of virus type, enumeration method, water temperature, and water type are provided for six virus families that had sufficient data available for model fitting (i.e., Coronaviridae, Phi6, Herpesviridae, Orthomyxoviridae, Rhabdoviridae, Togaviridae). Compiled log10k and multiple regression models can be used to inform management of human and animal waste, operation of water and wastewater facilities, and exposure risks to treatment plant workers and communities living in regions that lack treatment facilities. Given limited data available for some enveloped virus families with a potential water-related transmission route, there is need for additional data collection to aid academic researchers, public health agencies, and water and wastewater professionals involved in outbreak response.

Sunlight Inactivation of Human Norovirus and Bacteriophage MS2 Using a Genome-Wide PCR-Based Approach and Enzyme Pretreatment.

Human norovirus (hNoV) is an important etiology of gastrointestinal illness and can be transmitted via ingestion of contaminated water. Currently impractical to culture, hNoV detection is reliant on real-time polymerase chain reaction (RT-PCR)-based methods. This approach cannot distinguish between infective and inactivated viruses because intact regions of the RNA genome can amplify even if the damage is present in other regions of the genome or because intact genetic material is not contained within an infectious virion. Herein, we employ a multiple long-amplicon RT-qPCR extrapolation approach to assay genome-wide damage and an enzymatic pretreatment to study the impact of simulated sunlight on the infectivity of hNoV in clear, sensitizer-free water. Using MS2 coliphage as an internal control, the genome-wide damage extrapolation approach, previously successfully applied for UV-254 inactivation, vastly overestimated sunlight inactivation, suggesting key differences in photoinactivation under different spectral conditions. hNoV genomic RNA was more susceptible to simulated sunlight degradation per base compared to MS2 genomic RNA, while enzymatic pretreatment indicated that hNoV experienced more capsid damage than MS2. This work provides practical and mechanistic insight into the endogenous sunlight inactivation of single-stranded RNA bacteriophage MS2, a widely used surrogate, and hNoV GII.4 Sydney, an important health-relevant virus, in clear sensitizer-free water.

The Environmental Microbiology Minimum Information (EMMI) Guidelines: qPCR and dPCR Quality and Reporting for Environmental Microbiology.

Real-time quantitative polymerase chain reaction (qPCR) and digital PCR (dPCR) methods have revolutionized environmental microbiology, yielding quantitative organism-specific data of nucleic acid targets in the environment. Such data are essential for characterizing interactions and processes of microbial communities, assessing microbial contaminants in the environment (water, air, fomites), and developing interventions (water treatment, surface disinfection, air purification) to curb infectious disease transmission. However, our review of recent qPCR and dPCR literature in our field of health-related environmental microbiology showed that many researchers are not reporting necessary and sufficient controls and methods, which would serve to strengthen their study results and conclusions. Here, we describe the application, utility, and interpretation of the suite of controls needed to make high quality qPCR and dPCR measurements of microorganisms in the environment. Our presentation is organized by the discrete steps and operations typical of this measurement process. We propose systematic terminology to minimize ambiguity and aid comparisons among studies. Example schemes for batching and combining controls for efficient work flow are demonstrated. We describe critical reporting elements for enhancing data credibility, and we provide an element checklist in the Supporting Information. Additionally, we present several key principles in metrology as context for laboratories to devise their own quality assurance and quality control reporting framework. Following the EMMI guidelines will improve comparability and reproducibility among qPCR and dPCR studies in environmental microbiology, better inform engineering and public health actions for preventing disease transmission through environmental pathways, and for the most pressing issues in the discipline, focus the weight of evidence in the direction toward solutions.

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.