COVID-19 wastewater surveillance in rural communities: Comparison of lagoon and pumping station samples

Sewer transport conditions and their role in the decay of endogenous SARS-CoV-2 and pepper mild mottle virus from source to collection

This study presents a comprehensive analysis of the decay patterns of endogenous SARS-CoV-2 and Pepper mild mottle virus (PMMoV) within wastewaters spiked with stool from infected patients expressing COVID-19 symptoms, and hence explores the decay of endogenous SARS-CoV-2 and PMMoV targets in wastewaters from source to collection of the sample. Stool samples from infected patients were used as endogenous viral material to more accurately mirror real-world decay processes compared to more traditionally used lab-propagated spike-ins. As such, this study includes data on early decay stages of endogenous viral targets in wastewaters that are typically overlooked when performing decay studies on wastewaters harvested from wastewater treatment plants that contain already-degraded endogenous material. The two distinct sewer transport conditions of dynamic suspended sewer transport and bed and near-bed sewer transport were simulated in this study at temperatures of 4 °C, 12 °C and 20 °C to elucidate decay under these two dominant transport conditions within wastewater infrastructure. The dynamic suspended sewer transport was simulated over 35 h, representing typical flow conditions, whereas bed and near-bed transport extended to 60 days to reflect the prolonged settling of solids in sewer systems during reduced flow periods. In dynamic suspended sewer transport, no decay was observed for SARS-CoV-2, PMMoV, or total RNA over the 35-h period, and temperature ranging from 4 °C to 20 °C had no noticeable effect. Conversely, experiments simulating bed and near-bed transport conditions revealed significant decreases in SARS-CoV-2 and total RNA concentrations by day 2, and PMMoV concentrations by day 3. Only PMMoV exhibited a clear trend of increasing decay constant with higher temperatures, suggesting that while temperature influences decay dynamics, its impact may be less significant than previously assumed, particularly for endogenous RNA that is bound to dissolved organic matter in wastewater. First order decay models were inadequate for accurately fitting decay curves of SARS-CoV-2, PMMoV, and total RNA in bed and near-bed transport conditions. F-tests confirmed the superior fit of the two-phase decay model compared to first order decay models across temperatures of 4 °C-20 °C. Finally, and most importantly, total RNA normalization emerged as an appropriate approach for correcting the time decay of SARS-CoV-2 exposed to bed and near-bed transport conditions. These findings highlight the importance of considering decay from the point of entry in the sewers, sewer transport conditions, and normalization strategies when assessing and modelling the impact of viral decay rates in wastewater systems. This study also emphasizes the need for ongoing research into the diverse and multifaceted factors that influence these decay rates, which is crucial for accurate public health monitoring and response strategies.

Small-scale wastewater-based epidemiology (WBE) for infectious diseases and antibiotic resistance: A scoping review

Wastewater analysis can serve as a source of public health information. In recent years, wastewater-based epidemiology (WBE) has emerged and proven useful for the detection of infectious diseases. However, insights from the wastewater treatment plant do not allow for the small-scale differentiation within the sewer system that is needed to analyze the target population under study in more detail. Small-scale WBE offers several advantages, but there has been no systematic overview of its application. The aim of this scoping review is to provide a comprehensive overview of the current state of knowledge on small-scale WBE for infectious diseases, including methodological considerations for its application. A systematic database search was conducted, considering only peer-reviewed articles. Data analyses included quantitative summary and qualitative narrative synthesis. Of 2130 articles, we included 278, most of which were published since 2020. The studies analyzed wastewater at the building level (n = 203), especially healthcare (n = 110) and educational facilities (n = 80), and at the neighborhood scale (n = 86). The main analytical parameters were viruses (n = 178), notably SARS-CoV-2 (n = 161), and antibiotic resistance (ABR) biomarkers (n = 99), often analyzed by polymerase chain reaction (PCR), with DNA sequencing techniques being less common. In terms of sampling techniques, active sampling dominated. The frequent lack of detailed information on the specification of selection criteria and the characterization of the small-scale sampling sites was identified as a concern. In conclusion, based on the large number of studies, we identified several methodological considerations and overarching strategic aspects for small-scale WBE. An enabling environment for small-scale WBE requires inter- and transdisciplinary knowledge sharing across countries. Promoting the adoption of small-scale WBE will benefit from a common international conceptualization of the approach, including standardized and internationally accepted terminology. In particular, the development of good WBE practices for different aspects of small-scale WBE is warranted. This includes the establishment of guidelines for a comprehensive characterization of the local sewer system and its sub-sewersheds, and transparent reporting to ensure comparability of small-scale WBE results.

Fate-and-transport modeling of SARS-CoV-2 for rural wastewater-based epidemiology application benefit

Wastewater-based epidemiology (WBE) for the detection of agents of concern such as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been prevalent in literature since 2020. The majority of reported research focuses on large urban centers with few references to rural communities. In this research the EPA-Storm Water Management Model (EPA-SWMM) software was used to describe a small sewershed and identify the effects of temperature, temperature-affected decay rate, flow rate, flush time, fecal shedding rate, and historical infection rates during the spread of the Omicron variant of the SARS-CoV-2 virus within the sewershed. Due to the sewershed's relative isolation from the rest of the city, its wastewater quality behavior is similar to a rural sewershed. The model was used to assess city wastewater sampling campaigns to best appropriate field and or lab equipment when sampling wastewater. An important aspect of the assessment was the comparison of SARS-CoV-2 quantification methods with specifically between a traditional microbiological lab (practical quantitation limit, PQL, 1 GC/mL) versus what can be known from a field method (PQL 10 GC/mL). Understanding these monitoring choices will help rural communities make decisions on how to best implement the collection and testing for WBE agents of concern. An important outcome of this work is the knowledge that it is possible to simulate a WBE agent of concern with reasonable precision, if uncertainties are incorporated into model sensitivity. These ideas could form the basis for future mixed monitoring-modeling studies that will enhance its application and therefore adoption of WBE techniques in communities of many sizes and financial means.

Online trend estimation and detection of trend deviations in sub-sewershed time series of SARS-CoV-2 RNA measured in wastewater

Wastewater surveillance has proven a cost-effective key public health tool to understand a wide range of community health diseases and has been a strong source of information on community levels and spread for health departments throughout the SARS- CoV-2 pandemic. Studies spanning the globe demonstrate the strong association between virus levels observed in wastewater and quality clinical case information of the population served by the sewershed. Few of these studies incorporate the temporal dependence present in sampling over time, which can lead to estimation issues which in turn impact conclusions. We contribute to the literature for this important public health science by putting forward time series methods coupled with statistical process control that (1) capture the evolving trend of a disease in the population; (2) separate the uncertainty in the population disease trend from the uncertainty due to sampling and measurement; and (3) support comparison of sub-sewershed population disease dynamics with those of the population represented by the larger downstream treatment plant. Our statistical methods incorporate the fact that measurements are over time, ensuring correct statistical conclusions. We provide a retrospective example of how sub-sewersheds virus levels compare to the upstream wastewater treatment plant virus levels. An on-line algorithm supports real-time statistical assessment of deviations of virus level in a population represented by a sub-sewershed to the virus level in the corresponding larger downstream wastewater treatment plant. This information supports public health decisions by spotlighting segments of the population where outbreaks may be occurring.

Impact of coagulation on SARS-CoV-2 and PMMoV viral signal in wastewater solids

Wastewater surveillance (WWS) of SARS-CoV-2 has become a crucial tool for monitoring COVID-19 cases and outbreaks. Previous studies have indicated that SARS-CoV-2 RNA measurement from testing solid-rich primary sludge yields better sensitivity compared to testing wastewater influent. Furthermore, measurement of pepper mild mottle virus (PMMoV) signal in wastewater allows for precise normalization of SARS-CoV-2 viral signal based on solid content, enhancing disease prevalence tracking. However, despite the widespread adoption of WWS, a knowledge gap remains regarding the impact of ferric sulfate coagulation, commonly used in enhanced primary clarification, the initial stage of wastewater treatment where solids are sedimented and removed, on SARS-CoV-2 and PMMoV quantification in wastewater-based epidemiology. This study examines the effects of ferric sulfate addition, along with the associated pH reduction, on the measurement of SARS-CoV-2 and PMMoV viral measurements in wastewater primary clarified sludge through jar testing. Results show that the addition of Fe3+ concentrations in the conventional 0 to 60 mg/L range caused no effect on SARS-CoV-2 N1 and N2 gene region measurements in wastewater solids. However, elevated Fe3+ concentrations were shown to be associated with a statistically significant increase in PMMoV viral measurements in wastewater solids, which consequently resulted in the underestimation of PMMoV-normalized SARS-CoV-2 viral signal measurements (N1 and N2 copies/copies of PMMoV). The observed pH reduction from coagulant addition did not contribute to the increased PMMoV measurements, suggesting that this phenomenon arises from the partitioning of PMMoV viral particles into wastewater solids.

Wastewater-based surveillance identifies start to the pediatric respiratory syncytial virus season in two cities in Ontario, Canada

Introduction

Detection of community respiratory syncytial virus (RSV) infections informs the timing of immunoprophylaxis programs and hospital preparedness for surging pediatric volumes. In many jurisdictions, this relies upon RSV clinical test positivity and hospitalization (RSVH) trends, which are lagging indicators. Wastewater-based surveillance (WBS) may be a novel strategy to accurately identify the start of the RSV season and guide immunoprophylaxis administration and hospital preparedness.

Methods

We compared citywide wastewater samples and pediatric RSVH in Ottawa and Hamilton between August 1, 2022, and March 5, 2023. 24-h composite wastewater samples were collected daily and 5 days a week at the wastewater treatment facilities in Ottawa and Hamilton, Ontario, Canada, respectively. RSV WBS samples were analyzed in real-time for RSV by RT-qPCR.

Results

RSV WBS measurements in both Ottawa and Hamilton showed a lead time of 12 days when comparing the WBS data set to pediatric RSVH data set (Spearman's ρ = 0.90). WBS identify early RSV community transmission and declared the start of the RSV season 36 and 12 days in advance of the provincial RSV season start (October 31) for the city of Ottawa and Hamilton, respectively. The differing RSV start dates in the two cities is likely associated with geographical and regional variation in the incidence of RSV between the cities.

Discussion

Quantifying RSV in municipal wastewater forecasted a 12-day lead time of the pediatric RSVH surge and an earlier season start date compared to the provincial start date. These findings suggest an important role for RSV WBS to inform regional health system preparedness, reduce RSV burden, and understand variations in community-related illness as novel RSV vaccines and monoclonal antibodies become available.

Rapidly developed, optimized, and applied wastewater surveillance system for real-time monitoring of low-incidence, high-impact MPOX outbreak

Recent MPOX viral resurgences have mobilized public health agencies around the world. Recognizing the significant risk of MPOX outbreaks, large-scale human testing, and immunization campaigns have been initiated by local, national, and global public health authorities. Recently, traditional clinical surveillance campaigns for MPOX have been complemented with wastewater surveillance (WWS), building on the effectiveness of existing wastewater programs that were built to monitor SARS-CoV-2 and recently expanded to include influenza and respiratory syncytial virus surveillance in wastewaters. In the present study, we demonstrate and further support the finding that MPOX viral fragments agglomerate in the wastewater solids fraction. Furthermore, this study demonstrates that the current, most commonly used MPOX assays are equally effective at detecting low titers of MPOX viral signal in wastewaters. Finally, MPOX WWS is shown to be more effective at passively tracking outbreaks and/or resurgences of the disease than clinical testing alone in smaller communities with low human clinical case counts of MPOX.

Stabilization of SARS-CoV-2 RNA in wastewater via rapid RNA extraction

Wastewater-based Epidemiology (WBE) has contributed to surveillance of SARS-CoV-2 in communities across the world. Both symptomatic and asymptomatic patients with COVID-19 can shed the virus through the gastrointestinal tract, enabling the quantification of the virus in stool and ultimately in wastewater (WW). Unfortunately, instability of SARS-CoV-2 RNA in wastewater limits the utility of WBE programs, particularly in remote/rural regions where reliable cold storage and/or rapid shipping may be unavailable. This study examined whether rapid SARS-CoV-2 RNA extraction on the day of sample collection could minimize degradation. Importantly, the extraction technology used in these experiments, termed exclusion-based sample preparation (ESP), is lightweight, portable, and electricity-free, making it suitable for implementation in remote settings. We demonstrated that immediate RNA extraction followed by ambient storage significantly increased the RNA half-life compared to raw wastewater samples stored at both 4 °C or ambient temperature. Given that RNA degradation negatively impacts both the sensitivity and precision of WBE measurements, efforts must be made to mitigate degradation in order to maximize the potential impact of WBE on public health.

Significance of wastewater surveillance in detecting the prevalence of SARS-CoV-2 variants and other respiratory viruses in the community - A multi-site evaluation

Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral genome in wastewater has proven to be useful for tracking the trends of virus prevalence within the community. The surveillance also provides precise and early detection of any new and circulating variants, which aids in response to viral outbreaks. Site-specific monitoring of SARS-CoV-2 variants provides valuable information on the prevalence of new or emerging variants in the community. We sequenced the genomic RNA of viruses present in the wastewater samples and analyzed for the prevalence of SARS-CoV-2 variants as well as other respiratory viruses for a period of one year to account for seasonal variations. The samples were collected from the Reno-Sparks metropolitan area on a weekly basis between November 2021 to November 2022. Samples were analyzed to detect the levels of SARS-CoV-2 genomic copies and variants identification. This study confirmed that wastewater monitoring of SARS-CoV-2 variants can be used for community surveillance and early detection of circulating variants and supports wastewater-based epidemiology (WBE) as a complement to clinical respiratory virus testing as a healthcare response effort. Our study showed the persistence of the SARS-CoV-2 virus throughout the year compared to a seasonal presence of other respiratory viruses, implicating SARS-CoV-2's broad genetic diversity and strength to persist and infect susceptible hosts. Through secondary analysis, we further identified antimicrobial resistance (AMR) genes in the same wastewater samples and found WBE to be a feasible tool for community AMR detection and monitoring.

Norovirus, Hepatitis A and SARS-CoV-2 surveillance within Chilean rural wastewater treatment plants based on different biological treatment typologies

During the COVID-19 pandemic, wastewater from WWTPs became an interesting source of epidemiological surveillance. However, there is uncertainty about the influence of treatment type on virus removal. The aim of this study was to assess viral surveillance within wastewater treatment plants (WWTPs) based on different biological treatments. Seasonal monitoring (autumn-winter and spring-summer) was conducted in 10 Chilean rural WWTPs, which were based on activated sludge, aerated lagoons, bio-discs, constructed wetlands, vermifilters and mixed systems. Viruses were measured (influent/effluent) by the RT-qPCR technique, using a commercial kit for SARS-CoV-2, NoV GI, NoV GII, and HAV. The detection of SARS-CoV-2 viral variants by genotyping was performed using SARS-CoV-2 Mutation Assays (ThermoFisher Scientific, USA). JC polyomavirus detection (control), as well as a qPCR technique. Results showed that SARS-CoV-2, NoV GI and GII were detected in influents at values between <5 and 462, 0 to 28, and 0 to 75 GC/mL, respectively. HAV was not detected among the studied WWTPs. The monitored WWTPs removed these viruses at percentages between 0 and 100 %. WWTPs based on activated sludge with bio-discs demonstrated to be the most efficient at removing SARS-CoV-2 (up to 98 %) and NoV GI and GII (100 %). Meanwhile, bio-discs technologies were the least efficient for viral removal, due to biofilm detachment, which could also adsorb viral aggregates. A correlation analysis established that solids, pH, and temperature are the most influential parameters in viral removal. Wastewater-based surveillance at WWTP allowed for the detection of Omicron before the Chilean health authorities notified its presence in the population. In addition, surveillance of viruses and other microorganisms could help assess the potential public health risk of wastewater recycling.

A case study of a community-organized wastewater surveillance in a small community: correlating weekly reported COVID-19 cases with SARS-CoV-2 RNA concentrations during fall 2020 to summer 2021 in Yarmouth, ME

Wastewater surveillance offers a rapid evaluation of SARS-CoV-2 transmission in a community. We describe how a community group, the Yarmouth Wastewater Testing Team (YWTT), in Yarmouth, Maine, (population 8,990) utilized an asset-based community design framework to organize and manage a program to monitor SARS-CoV-2 RNA concentrations. From September 22, 2020 through June 8, 2021, the YWTT disseminated weekly reports of the wastewater results and reported COVID-19 cases within the Yarmouth postal code. After high and increasing SARS-CoV-2 RNA concentrations, the YWTT issued two community advisories to encourage extra care to reduce exposure. Correlations between SARS-CoV-2 RNA concentrations and COVID-19 cases were stronger the week after sampling, and the average of the COVID-19 cases during the week of sampling and the following week, indicating that surveillance provided advance notice of cases. A 10% increase in SARS-CoV-2 RNA concentrations was associated with a 13.29% increase in the average number of weekly reported cases of COVID-19 during the week of sampling and the following week (R2 = 0.42; p < 0.001). Adjusting for viral recovery (December 21, 2020 through June 8, 2021), improved R2 from 0.60 to 0.68. Wastewater surveillance was an effective tool for the YWTT to quickly respond to viral transmission.

Deep Learning Solution for Quantification of Fluorescence Particles on a Membrane

The detection and quantification of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus particles in ambient waters using a membrane-based in-gel loop-mediated isothermal amplification (mgLAMP) method can play an important role in large-scale environmental surveillance for early warning of potential outbreaks. However, counting particles or cells in fluorescence microscopy is an expensive, time-consuming, and tedious task that only highly trained technicians and researchers can perform. Although such objects are generally easy to identify, manually annotating cells is occasionally prone to fatigue errors and arbitrariness due to the operator's interpretation of borderline cases. In this research, we proposed a method to detect and quantify multiscale and shape variant SARS-CoV-2 fluorescent cells generated using a portable (mgLAMP) system and captured using a smartphone camera. The proposed method is based on the YOLOv5 algorithm, which uses CSPnet as its backbone. CSPnet is a recently proposed convolutional neural network (CNN) that duplicates gradient information within the network using a combination of Dense nets and ResNet blocks, and bottleneck convolution layers to reduce computation while at the same time maintaining high accuracy. In addition, we apply the test time augmentation (TTA) algorithm in conjunction with YOLO's one-stage multihead detection heads to detect all cells of varying sizes and shapes. We evaluated the model using a private dataset provided by the Linde + Robinson Laboratory, California Institute of Technology, United States. The model achieved a mAP@0.5 score of 90.3 in the YOLOv5-s6.

Does normalization of SARS-CoV-2 concentrations by Pepper Mild Mottle Virus improve correlations and lead time between wastewater surveillance and clinical data in Alberta (Canada): comparing twelve SARS-CoV-2 normalization approaches

Wastewater-based surveillance (WBS) data normalization is an analyte measurement correction that addresses variations resulting from dilution of fecal discharge by non-sanitary sewage, stormwater or groundwater infiltration. No consensus exists on what WBS normalization parameters result in the strongest correlations and lead time between SARS-CoV-2 WBS data and COVID-19 cases. This study compared flow, population size and biomarker normalization impacts on the correlations and lead times for ten communities in twelve sewersheds in Alberta (Canada) between September 2020 and October 2021 (n = 1024) to determine if normalization by Pepper Mild Mottle Virus (PMMoV) provides any advantages compared to other normalization parameters (e.g., flow, reported and dynamic population sizes, BOD, TSS, NH3, TP). PMMoV concentrations (GC/mL) corresponded with plant influent flows and were highest in the urban centres. SARS-CoV-2 target genes E, N1 and N2 were all negatively associated with wastewater influent pH, while PMMoV was positively associated with temperature. Pooled data analysis showed that normalization increased ρ-values by almost 0.1 and was highest for ammonia, TKN and TP followed by PMMoV. Normalization by other parameters weakened associations. None of the differences were statistically significant. Site-specific correlations showed that normalization of SARS-CoV-2 data by PMMoV only improved correlations significantly in two of the twelve systems; neither were large sewersheds or combined sewer systems. In five systems, normalization by traditional wastewater strength parameters and dynamic population estimates improved correlations. Lead time ranged between 1 and 4 days in both pooled and site-specific comparisons. We recommend that WBS researchers and health departments: a) Investigate WWTP influent properties (e.g., pH) in the WBS planning phase and use at least two parallel approaches for normalization only if shown to provide value; b) Explore normalization by wastewater strength parameters and dynamic population size estimates further; and c) Evaluate purchasing an influent flow meter in small communities to support long-term WBS efforts and WWTP management.

Direct wastewater extraction as a simple and effective method for SARS-CoV-2 surveillance and COVID-19 community-level monitoring

Wastewater surveillance has proven to be an effective tool to monitor the transmission and emergence of infectious agents at a community scale. Workflows for wastewater surveillance generally rely on concentration steps to increase the probability of detection of low-abundance targets, but preconcentration can substantially increase the time and cost of analyses while also introducing additional loss of target during processing. To address some of these issues, we conducted a longitudinal study implementing a simplified workflow for SARS-CoV-2 detection from wastewater, using a direct column-based extraction approach. Composite influent wastewater samples were collected weekly for 1 year between June 2020 and June 2021 in Athens-Clarke County, Georgia, USA. Bypassing any concentration step, low volumes (280 µl) of influent wastewater were extracted using a commercial kit, and immediately analyzed by RT-qPCR for the SARS-CoV-2 N1 and N2 gene targets. SARS-CoV-2 viral RNA was detected in 76% (193/254) of influent samples, and the recovery of the surrogate bovine coronavirus was 42% (IQR: 28%, 59%). N1 and N2 assay positivity, viral concentration, and flow-adjusted daily viral load correlated significantly with per-capita case reports of COVID-19 at the county-level (ρ = 0.69-0.82). To compensate for the method's high limit of detection (approximately 106-107 copies l-1 in wastewater), we extracted multiple small-volume replicates of each wastewater sample. With this approach, we detected as few as five cases of COVID-19 per 100 000 individuals. These results indicate that a direct-extraction-based workflow for SARS-CoV-2 wastewater surveillance can provide informative and actionable results.

Understanding the dynamic relation between wastewater SARS-CoV-2 signal and clinical metrics throughout the pandemic

Wastewater surveillance (WWS) of SARS-CoV-2 was proven to be a reliable and complementary tool for population-wide monitoring of COVID-19 disease incidence but was not as rigorously explored as an indicator for disease burden throughout the pandemic. Prior to global mass immunization campaigns and during the spread of the wildtype COVID-19 and the Alpha variant of concern (VOC), viral measurement of SARS-CoV-2 in wastewater was a leading indicator for both COVID-19 incidence and disease burden in communities. As the two-dose vaccination rates escalated during the spread of the Delta VOC in Jul. 2021 through Dec. 2021, relations weakened between wastewater signal and community COVID-19 disease incidence and maintained a strong relationship with clinical metrics indicative of disease burden (new hospital admissions, ICU admissions, and deaths). Further, with the onset of the vaccine-resistant Omicron BA.1 VOC in Dec. 2021 through Mar. 2022, wastewater again became a strong indicator of both disease incidence and burden during a period of limited natural immunization (no recent infection), vaccine escape, and waned vaccine effectiveness. Lastly, with the populations regaining enhanced natural and vaccination immunization shortly prior to the onset of the Omicron BA.2 VOC in mid-Mar 2022, wastewater is shown to be a strong indicator for both disease incidence and burden. Hospitalization-to-wastewater ratio is further shown to be a good indicator of VOC virulence when widespread clinical testing is limited. In the future, WWS is expected to show moderate indication of incidence and strong indication of disease burden in the community during future potential seasonal vaccination campaigns.

Wastewater to clinical case (WC) ratio of COVID-19 identifies insufficient clinical testing, onset of new variants of concern and population immunity in urban communities

Clinical testing has been the cornerstone of public health monitoring and infection control efforts in communities throughout the COVID-19 pandemic. With the anticipated reduction of clinical testing as the disease moves into an endemic state, SARS-CoV-2 wastewater surveillance (WWS) will have greater value as an important diagnostic tool. An in-depth analysis and understanding of the metrics derived from WWS is required to interpret and utilize WWS-acquired data effectively (McClary-Gutierrez et al., 2021; O'Keeffe, 2021). In this study, the SARS-CoV-2 wastewater signal to clinical cases (WC) ratio was investigated across seven cities in Canada over periods ranging from 8 to 21 months. This work demonstrates that significant increases in the WC ratio occurred when clinical testing eligibility was modified to appointment-only testing, identifying a period of insufficient clinical testing (resulting in a reduction to testing access and a reduction in the number of daily tests) in these communities, despite increases in the wastewater signal. Furthermore, the WC ratio decreased significantly in 6 of the 7 studied locations, serving as a potential signal of the emergence of the Alpha variant of concern (VOC) in a relatively non-immunized community (40-60 % allelic proportion), while a more muted decrease in the WC ratio signaled the emergence of the Delta VOC in a relatively well-immunized community (40-60 % allelic proportion). Finally, a significant decrease in the WC ratio signaled the emergence of the Omicron VOC, likely because of the variant's greater effectiveness at evading immunity, leading to a significant number of new reported clinical cases, even when community immunity was high. The WC ratio, used as an additional monitoring metric, could complement clinical case counts and wastewater signals as individual metrics in its potential ability to identify important epidemiological occurrences, adding value to WWS as a diagnostic technology during the COVID-19 pandemic and likely for future pandemics.

Wastewater-based epidemiological surveillance to monitor the prevalence of SARS-CoV-2 in developing countries with onsite sanitation facilities

Wastewater-based epidemiology (WBE) has emerged as a valuable approach for forecasting disease outbreaks in developed countries with a centralized sewage infrastructure. On the other hand, due to the absence of well-defined and systematic sewage networks, WBE is challenging to implement in developing countries like Bangladesh where most people live in rural areas. Identification of appropriate locations for rural Hotspot Based Sampling (HBS) and urban Drain Based Sampling (DBS) are critical to enable WBE based monitoring system. We investigated the best sampling locations from both urban and rural areas in Bangladesh after evaluating the sanitation infrastructure for forecasting COVID-19 prevalence. A total of 168 wastewater samples were collected from 14 districts of Bangladesh during each of the two peak pandemic seasons. RT-qPCR commercial kits were used to target ORF1ab and N genes. The presence of SARS-CoV-2 genetic materials was found in 98% (165/168) and 95% (160/168) wastewater samples in the first and second round sampling, respectively. Although wastewater effluents from both the marketplace and isolation center drains were found with the highest amount of genetic materials according to the mixed model, quantifiable SARS-CoV-2 RNAs were also identified in the other four sampling sites. Hence, wastewater samples of the marketplace in rural areas and isolation centers in urban areas can be considered the appropriate sampling sites to detect contagion hotspots. This is the first complete study to detect SARS-CoV-2 genetic components in wastewater samples collected from rural and urban areas for monitoring the COVID-19 pandemic. The results based on the study revealed a correlation between viral copy numbers in wastewater samples and SARS-CoV-2 positive cases reported by the Directorate General of Health Services (DGHS) as part of the national surveillance program for COVID-19 prevention. The findings of this study will help in setting strategies and guidelines for the selection of appropriate sampling sites, which will facilitate in development of comprehensive wastewater-based epidemiological systems for surveillance of rural and urban areas of low-income countries with inadequate sewage infrastructure.

Testing specificity and sensitivity of wastewater-based epidemiology for detecting SARS-CoV-2 in four communities on Vancouver Island, Canada

We report wastewater surveillance of the spread of SARS-CoV-2 based upon 24-h composite influent samples taken weekly from four wastewater treatment plants (WWTP) on Vancouver Island, BC, Canada between January 3, 2021 and July 10, 2021. Samples were analyzed by reverse transcription quantitative polymerase chain reaction targeting the N1 and N2 gene fragments of SARS-CoV-2 and a region of the replication associate protein of the pepper mottle mosaic virus (PMMoV) serving as endemic control. Only a small proportion of samples had quantifiable levels of N1 or N2. Overall case rates are weakly correlated with the concentration (gene copies/L) and with the flux of viral material influent to the WWTP (gene copies/day); the latter accounts for influent flow variations. Poisson multimodal rank correlation accounts for differences between the four WWTP and shows a significant correlation with a significant positive intercept. Receiver operator characteristics (ROC) analysis confirms a cut-off of cases based on amplified/not-amplified experimental data. At the optimal cut point of 19 (N1) or 17 (N2) cases/week/100,000 the sensitivity and specificity is about 75% for N1 and 67% for N2.

Municipal and neighbourhood level wastewater surveillance and subtyping of an influenza virus outbreak

Recurrent influenza epidemics and pandemic potential are significant risks to global health. Public health authorities use clinical surveillance to locate and monitor influenza and influenza-like cases and outbreaks to mitigate hospitalizations and deaths. Currently, global integration of clinical surveillance is the only reliable method for reporting influenza types and subtypes to warn of emergent pandemic strains. The utility of wastewater surveillance (WWS) during the COVID-19 pandemic as a less resource intensive replacement or complement for clinical surveillance has been predicated on analyzing viral fragments in wastewater. We show here that influenza virus targets are stable in wastewater and partitions favorably to the solids fraction. By quantifying, typing, and subtyping the virus in municipal wastewater and primary sludge during a community outbreak, we forecasted a citywide flu outbreak with a 17-day lead time and provided population-level viral subtyping in near real-time to show the feasibility of influenza virus WWS at the municipal and neighbourhood levels in near real time using minimal resources and infrastructure.

Municipal and neighbourhood level wastewater surveillance and subtyping of an influenza virus outbreak

Recurrent influenza epidemics and pandemic potential are significant risks to global health. Public health authorities use clinical surveillance to locate and monitor influenza and influenza-like cases and outbreaks to mitigate hospitalizations and deaths. Currently, global integration of clinical surveillance is the only reliable method for reporting influenza types and subtypes to warn of emergent pandemic strains. The utility of wastewater surveillance (WWS) during the COVID-19 pandemic as a less resource intensive replacement or complement for clinical surveillance has been predicated on analyzing viral fragments in wastewater. We show here that influenza virus targets are stable in wastewater and partitions favorably to the solids fraction. By quantifying, typing, and subtyping the virus in municipal wastewater and primary sludge during a community outbreak, we forecasted a citywide flu outbreak with a 17-day lead time and provided population-level viral subtyping in near real-time to show the feasibility of influenza virus WWS at the municipal and neighbourhood levels in near real time using minimal resources and infrastructure.

The need of an environmental justice approach for wastewater based epidemiology for rural and disadvantaged communities: A review in California

Amid the 2019 coronavirus disease pandemic (COVID-19), the scientific community has a responsibility to provide accessible public health resources within their communities. Wastewater based epidemiology (WBE) has been used to monitor community spread of the pandemic. The goal of this review was to evaluate the need for an environmental justice approach for COVID-19 WBE starting with the state of California in the United States. Methods included a review of the peer-reviewed literature, government-provided data, and news stories. As of June 2021, there were twelve universities, nine public dashboards, and 48 of 384 wastewater treatment plants monitoring wastewater for SARS-CoV-2 within California. The majority of wastewater monitoring in California has been conducted in the urban areas of Coastal and Southern California (34/48), with a lack of monitoring in more rural areas of Central (10/48) and Northern California (4/48). Similar to the access to COVID-19 clinical testing and vaccinations, there is a disparity in access to wastewater testing which can often provide an early warning system to outbreaks. This research demonstrates the need for an environmental justice approach and equity considerations when determining locations for environmental monitoring.

Detection of SARS-CoV-2 RNA in wastewater and importance of population size assessment in smaller cities: An exploratory case study from two municipalities in Latvia

Wastewater-based epidemiology (WBE) has regained global importance during the COVID-19 pandemic. The mobility of people and other factors, such as precipitation and irregular inflow of industrial wastewater, are complicating the estimation of the disease prevalence through WBE, which is crucial for proper crisis management. These estimations are particularly challenging in urban areas with moderate or low numbers of inhabitants in situations where movement restrictions are not adopted (as in the case of Latvia) because residents of smaller municipalities tend to be more mobile and less strict in following the rules and measures of disease containment. Thus, population movement can influence the outcome of WBE measurements significantly and may not reflect the actual epidemiological situation in the respective area. Here, we demonstrate that by combining the data of detected SARS-CoV-2 RNA copy number, 5-hydroxyindoleacetic acid (5-HIAA) analyses in wastewater and mobile call detail records it was possible to provide an accurate assessment of the COVID-19 epidemiological situation in towns that are small (COVID-19 28-day cumulative incidence r = 0.609 and 35-day cumulative incidence r = 0.89, p < 0.05) and medium-sized towns (COVID-19 21-day cumulative incidence r = 0.997, 28-day cumulative incidence r = 0.98 and 35-day cumulative incidence r = 0.997, p < 0.05). This is the first study demonstrating WBE for monitoring COVID-19 outbreaks in Latvia. We demonstrate that the application of population size estimation measurements such as total 5-HIAA and call detail record data improve the accuracy of the WBE approach.

Wastewater Surveillance for SARS-CoV-2 RNA in Canada

Wastewater surveillance for SARS-CoV-2 RNA is a relatively recent adaptation of long-standing wastewater surveillance for infectious and other harmful agents. Individuals infected with COVID-19 were found to shed SARS-CoV-2 in their faeces. Researchers around the world confirmed that SARS-CoV-2 RNA fragments could be detected and quantified in community wastewater. Canadian academic researchers, largely as volunteer initiatives, reported proof-of-concept by April 2020. National collaboration was initially facilitated by the Canadian Water Network.

Many public health officials were initially skeptical about actionable information being provided by wastewater surveillance even though experience has shown that public health surveillance for a pandemic has no single, perfect approach. Rather, different approaches provide different insights, each with its own strengths and limitations. Public health science must triangulate among different forms of evidence to maximize understanding of what is happening or may be expected. Well-conceived, resourced, and implemented wastewater-based platforms can provide a cost-effective approach to support other conventional lines of evidence. Sustaining wastewater monitoring platforms for future surveillance of other disease targets and health states is a challenge. Canada can benefit from taking lessons learned from the COVID-19 pandemic to develop forward-looking interpretive frameworks and capacity to implement, adapt, and expand such public health surveillance capabilities.

Near real-time determination of B.1.1.7 in proportion to total SARS-CoV-2 viral load in wastewater using an allele-specific primer extension PCR strategy

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed millions of lives to date. Antigenic drift has resulted in viral variants with putatively greater transmissibility, virulence, or both. Early and near real-time detection of these variants of concern (VOC) and the ability to accurately follow their incidence and prevalence in communities is wanting. Wastewater-based epidemiology (WBE), which uses nucleic acid amplification tests to detect viral fragments, is a reliable proxy of COVID-19 incidence and prevalence, and thus offers the potential to monitor VOC viral load in a given population. Here, we describe and validate a primer extension PCR strategy targeting a signature mutation in the N gene of SARS-CoV-2. This allows quantification of B.1.1.7 versus non-B.1.1.7 allele frequency in wastewater without the need to employ quantitative RT-PCR standard curves. We show that the wastewater B.1.1.7 profile correlates with its clinical counterpart and benefits from a near real-time and facile data collection and reporting pipeline. This assay can be quickly implemented within a current SARS-CoV-2 WBE framework with minimal cost; allowing early and contemporaneous estimates of B.1.1.7 community transmission prior to, or in lieu of, clinical screening and identification. Our study demonstrates that this strategy can provide public health units with an additional and much needed tool to rapidly triangulate VOC incidence/prevalence with high sensitivity and lineage specificity.