City-level SARS-CoV-2 sewage surveillance

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.

Human adenovirus outbreak at a university campus monitored by wastewater and clinical surveillance

Areas of dense population congregation are prone to experience respiratory virus outbreaks. We monitored wastewater and clinic patients for the presence of respiratory viruses on a large, public university campus. Campus sewer systems were monitored in 16 locations for the presence of viruses using next generation sequencing over 22 weeks in 2023. During this period, we detected a surge in human adenovirus (HAdV) levels in wastewater. Hence, we initiated clinical surveillance at an on-campus clinic from patients presenting with acute respiratory infection. From whole genome sequencing of 123 throat and/or nasal swabs collected, we identified an outbreak of HAdV, specifically of HAdV-E4 and HAdV-B7 genotypes overlapping in time. The temporal dynamics and proportions of HAdV genotypes found in wastewater were corroborated in clinical infections. We tracked specific single nucleotide polymorphisms (SNPs) found in clinical virus sequences and showed that they arose in wastewater signals concordant with the time of clinical presentation, linking community transmission of HAdV to the outbreak. This study demonstrates how wastewater-based epidemiology can be integrated with surveillance at ambulatory healthcare settings to monitor areas prone to respiratory virus outbreaks and provide public health guidance.

Wastewater-based surveillance as a tool for public health action: SARS-CoV-2 and beyond

Wastewater-based surveillance (WBS) has undergone dramatic advancement in the context of the coronavirus disease 2019 (COVID-19) pandemic. The power and potential of this platform technology were rapidly realized when it became evident that not only did WBS-measured SARS-CoV-2 RNA correlate strongly with COVID-19 clinical disease within monitored populations but also, in fact, it functioned as a leading indicator. Teams from across the globe rapidly innovated novel approaches by which wastewater could be collected from diverse sewersheds ranging from wastewater treatment plants (enabling community-level surveillance) to more granular locations including individual neighborhoods and high-risk buildings such as long-term care facilities (LTCF). Efficient processes enabled SARS-CoV-2 RNA extraction and concentration from the highly dilute wastewater matrix. Molecular and genomic tools to identify, quantify, and characterize SARS-CoV-2 and its various variants were adapted from clinical programs and applied to these mixed environmental systems. Novel data-sharing tools allowed this information to be mobilized and made immediately available to public health and government decision-makers and even the public, enabling evidence-informed decision-making based on local disease dynamics. WBS has since been recognized as a tool of transformative potential, providing near-real-time cost-effective, objective, comprehensive, and inclusive data on the changing prevalence of measured analytes across space and time in populations. However, as a consequence of rapid innovation from hundreds of teams simultaneously, tremendous heterogeneity currently exists in the SARS-CoV-2 WBS literature. This manuscript provides a state-of-the-art review of WBS as established with SARS-CoV-2 and details the current work underway expanding its scope to other infectious disease targets.

The Israeli health system's rapid responses during the COVID-19 pandemic

BACKGROUND

The COVID-19 pandemic posed numerous challenges to health systems around the world. In addressing many of those challenges, Israel responded quite rapidly. While quick action is not an end in it itself, it can be important in responding to disease outbreaks. Some of Israel's rapid responses to the pandemic contributed significantly to population health and provided important learning opportunities for other countries.

MAIN BODY

Some of the most prominent Israeli rapid responses were related to vaccination. Israel led the world in the pace of its initial vaccine rollout, and it was also the first country to approve and administer booster vaccines to broad segments of the population. In addition, Israeli scholars published a series of timely reports analyzing vaccination impact, which informed policy in Israel and other countries. Israel was a rapid responder in additional areas of public health. These include the partial closure of its borders, the adoption of physical distancing measures, the use of digital surveillance technology for contact tracing, the use of wastewater surveillance to monitor viral spread, and the use of vaccine certificates ("green passes") to facilitate a return to routine in the face of the ongoing pandemic. Many factors contributed to Israel's capacity to repeatedly respond rapidly to a broad array of COVID-19 challenges. These include a national health insurance system that promotes public-private coordination, a system of universal electronic health records, a high level of emergency preparedness, a culture of focusing on goal attainment, a culture of innovation, and the presence of a strong scientific community which is highly connected internationally. In addition, some of the rapid responses (e.g., the rapid initial vaccination rollout) facilitated rapid responses in related areas (e.g., the analysis of vaccination impact, the administration of boosters, and the adoption of green passes). While rapid response can contribute to population health and economic resilience, it can also entail costs, risks, and limitations. These include making decisions and acting before all the relevant information is available; deciding without sufficient consideration of the full range of possible effects, costs, and benefits; not providing enough opportunities for the involvement of relevant groups in the decision-making process; and depleting non-renewable resources.

CONCLUSIONS

Based on our findings, we encourage leaders in the Israeli government to ensure that its emergency response system will continue to have the capacity to respond rapidly to large-scale challenges, whether of a military or civilian nature. At the same time, the emergency response systems should develop mechanisms to include more stakeholders in the fast-paced decision-making process and should improve communication with the public. In addition, they should put into place mechanisms for timely reconsideration, adjustment, and-when warranted-reversal of decisions which, while reasonable when reached, turn out to have been ill-advised in the light of subsequent developments and evidence. These mechanisms could potentially involve any or all branches of government, as well as the public, the press, and professional organizations. Our findings also have implications for health system leaders in other countries. The Israeli experience can help them identify key capacities to develop during non-emergency periods, thus positioning themselves to respond more rapidly in an emergency. Finally, health system leaders in other countries could monitor Israel's rapid responses to future global health emergencies and adopt selected actions in their own countries.

Optimal Selection of Sampling Points within Sewer Networks for Wastewater-Based Epidemiology Applications

Wastewater-based epidemiology (WBE) has great potential to monitor community public health, especially during pandemics. However, it faces substantial hurdles in pathogen surveillance through WBE, encompassing data representativeness, spatiotemporal variability, population estimates, pathogen decay, and environmental factors. This paper aims to enhance the reliability of WBE data, especially for early outbreak detection and improved sampling strategies within sewer networks. The tool implemented in this paper combines a monitoring model and an optimization model to facilitate the optimal selection of sampling points within sewer networks. The monitoring model utilizes parameters such as feces density and average water consumption to define the detectability of the virus that needs to be monitored. This allows for standardization and simplicity in the process of moving from the analysis of wastewater samples to the identification of infection in the source area. The entropy-based model can select optimal sampling points in a sewer network to obtain the most specific information at a minimum cost. The practicality of our tool is validated using data from Hildesheim, Germany, employing SARS-CoV-2 as a pilot pathogen. It is important to note that the tool's versatility empowers its extension to monitor other pathogens in the future.

The Rise and Fall of Omicron BA.1 Variant as Seen in Wastewater Supports Epidemiological Model Predictions

The COVID-19 pandemic caused by the SARS-CoV-2 virus has inflicted significant mortality and morbidity worldwide. Continuous virus mutations have led to the emergence of new variants. The Omicron BA.1 sub-lineage prevailed as the dominant variant globally at the beginning of 2022 but was subsequently replaced by BA.2 in numerous countries. Wastewater-based epidemiology (WBE) offers an efficient tool for capturing viral shedding from infected individuals, enabling early detection of potential pandemic outbreaks without relying solely on community cooperation and clinical testing resources. This study integrated RT-qPCR assays for detecting general SARS-CoV-2 and its variants levels in wastewater into a modified triple susceptible-infected-recovered-susceptible (SIRS) model. The emergence of the Omicron BA.1 variant was observed, replacing the presence of its predecessor, the Delta variant. Comparative analysis between the wastewater data and the modified SIRS model effectively described the BA.1 and subsequent BA.2 waves, with the decline of the Delta variant aligning with its diminished presence below the detection threshold in wastewater. This study demonstrates the potential of WBE as a valuable tool for future pandemics. Furthermore, by analyzing the sensitivity of different variants to model parameters, we are able to deduce real-life values of cross-variant immunity probabilities, emphasizing the asymmetry in their strength.

ResNet14Attention network for identifying the titration end-point of potassium dichromate

With the rapid development of industry, the increasing discharge of sewage causes the detection of water quality to be of increasing importance. Potassium dichromate titration is one of the most important testing methods in water quality detection; the ability to accurately identify the titration end-point of potassium dichromate is currently a research challenge. To identify titration end-point quickly and accurately, this study proposes a ResNet14Attention network, which utilizes residual modules that focus on original image information and an attention mechanism that focuses highly on classification targets. The proposed ResNet14Attention network is compared with 12 convolutional neural networks such as ResNet series networks, VGG, and GoogLeNet. The results of comparison experiments reveal that only the proposed ResNet14Attention network has the highest training and testing accuracy of 100% among all convolutional neural networks in the comparison experiment; the proposed ResNet14Attention network has the highest training speed compared to all the networks that over 90% accuracy.

Wastewater early warning system for SARS-CoV-2 outbreaks and variants in a Coruña, Spain

Wastewater-based epidemiology has been widely used as a cost-effective method for tracking the COVID-19 pandemic at the community level. Here we describe COVIDBENS, a wastewater surveillance program running from June 2020 to March 2022 in the wastewater treatment plant of Bens in A Coruña (Spain). The main goal of this work was to provide an effective early warning tool based in wastewater epidemiology to help in decision-making at both the social and public health levels. RT-qPCR procedures and Illumina sequencing were used to weekly monitor the viral load and to detect SARS-CoV-2 mutations in wastewater, respectively. In addition, own statistical models were applied to estimate the real number of infected people and the frequency of each emerging variant circulating in the community, which considerable improved the surveillance strategy. Our analysis detected 6 viral load waves in A Coruña with concentrations between 10³ and 10⁶ SARS-CoV-2 RNA copies/L. Our system was able to anticipate community outbreaks during the pandemic with 8-36 days in advance with respect to clinical reports and, to detect the emergence of new SARS-CoV-2 variants in A Coruña such as Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (B.1.1.529 and BA.2) in wastewater with 42, 30, and 27 days, respectively, before the health system did. Data generated here helped local authorities and health managers to give a faster and more efficient response to the pandemic situation, and also allowed important industrial companies to adapt their production to each situation. The wastewater-based epidemiology program developed in our metropolitan area of A Coruña (Spain) during the SARS-CoV-2 pandemic served as a powerful early warning system combining statistical models with mutations and viral load monitoring in wastewater over time.

20-Month monitoring of SARS-CoV-2 in wastewater of Curitiba, in Southern Brazil

The COVID-19 pandemic resulted in the collapse of healthcare systems and led to the development and application of several approaches of wastewater-based epidemiology to monitor infected populations. The main objective of this study was to carry out a SARS-CoV-2 wastewater based surveillance in Curitiba, Southern Brazil Sewage samples were collected weekly for 20 months at the entrance of five treatment plants representing the entire city and quantified by qPCR using the N1 marker. The viral loads were correlated with epidemiological data. The correlation by sampling points showed that the relationship between the viral loads and the number of reported cases was best described by a cross-correlation function, indicating a lag between 7 and 14 days amidst the variables, whereas the data for the entire city presented a higher correlation (0.84) with the number of positive tests at lag 0 (sampling day). The results also suggest that the Omicron VOC resulted in higher titers than the Delta VOC. Overall, our results showed that the approach used was robust as an early warning system, even with the use of different epidemiological indicators or changes in the virus variants in circulation. Therefore, it can contribute to public decision-makers and health interventions, especially in vulnerable and low-income regions with limited clinical testing capacity. Looking toward the future, this approach will contribute to a new look at environmental sanitation and should even induce an increase in sewage coverage rates in emerging countries.

The dynamic relationship between COVID-19 cases and SARS-CoV-2 wastewater concentrations across time and space: Considerations for model training data sets

During the COVID-19 pandemic, wastewater-based surveillance has been used alongside diagnostic testing to monitor infection rates. With the decline in cases reported to public health departments due to at-home testing, wastewater data may serve as the primary input for epidemiological models, but training these models is not straightforward. We explored factors affecting noise and bias in the ratio between wastewater and case data collected in 26 sewersheds in California from October 2020 to March 2022. The strength of the relationship between wastewater and case data appeared dependent on sampling frequency and population size, but was not increased by wastewater normalization to flow rate or case count normalization to testing rates. Additionally, the lead and lag times between wastewater and case data varied over time and space, and the ratio of log-transformed individual cases to wastewater concentrations changed over time. This ratio decreased between the Epsilon/Alpha and Delta variant surges of COVID-19 and increased during the Omicron BA.1 variant surge, and was also related to the diagnostic testing rate. Based on this analysis, we present a framework of scenarios describing the dynamics of the case to wastewater ratio to aid in data handling decisions for ongoing modeling efforts.

Wastewater surveillance of SARS-CoV-2 at intra-city level demonstrated high resolution in tracking COVID-19 and calibration using chemical indicators

Wastewater-based epidemiology has proven to be a supportive tool to better comprehend the dynamics of the COVID-19 pandemic. As the disease moves into endemic stage, the surveillance at wastewater sub-catchments such as pump station and manholes is providing a novel mechanism to examine the reemergence and to take measures that can prevent the spread. However, there is still a lack of understanding when it comes to wastewater-based epidemiology implementation at the smaller intra-city level for better granularity in data, and dilution effect of rain precipitation at pump stations. For this study, grab samples were collected from six areas of Seattle between March-October 2021. These sampling sites comprised five manholes and one pump station with population ranging from 2580 to 39,502 per manhole/pump station. The wastewater samples were analyzed for SARS-CoV-2 RNA concentrations, and we also obtained the daily COVID-19 cases (from individual clinical testing) for each corresponding sewershed, which ranged from 1 to 12 and the daily incidence varied between 3 and 64 per 100,000 of population. Rain precipitation lowered viral RNA levels and sensitivity of viral detection but wastewater total ammonia (NH₄⁺-N) and phosphate (PO₄^3--P) were shown as potential chemical indicators to calibrate/level out the dilution effect. These chemicals showed the potential in improving the wastewater surveillance capacity of COVID-19.

Normalisation of SARS-CoV-2 concentrations in wastewater: The use of flow, electrical conductivity and crAssphage

Over the course of the Corona Virus Disease-19 (COVID-19) pandemic in 2020-2022, monitoring of the severe acute respiratory syndrome coronavirus 2 ribonucleic acid (SARS-CoV-2 RNA) in wastewater has rapidly evolved into a supplementary surveillance instrument for public health. Short term trends (2 weeks) are used as a basis for policy and decision making on measures for dealing with the pandemic. Normalisation is required to account for the dilution rate of the domestic wastewater that can strongly vary due to time- and location-dependent sewer inflow of runoff, industrial discharges and extraneous waters. The standard approach in sewage surveillance is normalisation using flow measurements, although flow based normalisation is not effective in case the wastewater volume sampled does not match the wastewater volume produced. In this paper, two alternative normalisation methods, using electrical conductivity and crAssphage have been studied and compared with the standard approach using flow measurements. For this, a total of 1116 24-h flow-proportional samples have been collected between September 2020 and August 2021 at nine monitoring locations. In addition, 221 stool samples have been analysed to determine the daily crAssphage load per person. Results show that, although crAssphage shedding rates per person vary greatly, on a population-level crAssphage loads per person per day were constant over time and similar for all catchments. Consequently, crAssphage can be used as a quantitative biomarker for populations above 5595 persons. Electrical conductivity is particularly suitable to determine dilution rates relative to dry weather flow concentrations. The overall conclusion is that flow normalisation is necessary to reliably determine short-term trends in virus circulation, and can be enhanced using crAssphage and/or electrical conductivity measurement as a quality check.

Whole campus wastewater surveillance of SARS-CoV-2 for COVID-19 outbreak management

In this long-term study (eight months), a wastewater-based epidemiology program was initiated as a decision support tool for the detection and containment of COVID-19 spread in the Technion campus. The on-campus students' accommodations (∼3,300 residents) were divided into housing clusters and monitored through wastewater SARS-CoV-2 surveillance in 10 manholes. Results were used to create a 'traffic-light' scheme allowing the Technion's COVID-19 task force to track COVID-19 spatiotemporal spread on the campus, and consequently, contain it before high morbidity levels develop. Of the 523 sewage samples analysed, 87.4% were negative for SARS-CoV-2 while 11.5% were positive, corroborating morbidity information the COVID-19 task force had. For 7.6% of the SARS-CoV-2 positive samples, the task force had no information about positive resident/s. In these events, new cases were identified after the relevant residents were clinically surge tested for COVID-19. Hence, in these instances, wastewater surveillance provided early warning helping to secure the health of the campus residents by minimising COVID-19 spread. The inflammation biomarker ferritin levels in SARS-CoV-2 positive sewage samples were significantly higher than in negative ones. This may indicate that in the future, ferritin (and other biomarkers) concentrations in wastewater could serve as indicators of infectious and inflammatory disease outbreaks.

Citywide wastewater SARS-CoV-2 levels strongly correlated with multiple disease surveillance indicators and outcomes over three COVID-19 waves

Public health surveillance systems for COVID-19 are multifaceted and include multiple indicators reflective of different aspects of the burden and spread of the disease in a community. With the emergence of wastewater disease surveillance as a powerful tool to track infection dynamics of SARS-CoV-2, there is a need to integrate and validate wastewater information with existing disease surveillance systems and demonstrate how it can be used as a routine surveillance tool. A first step toward integration is showing how it relates to other disease surveillance indicators and outcomes, such as case positivity rates, syndromic surveillance data, and hospital bed use rates. Here, we present an 86-week long surveillance study that covers three major COVID-19 surges. City-wide SARS-CoV-2 RNA viral loads in wastewater were measured across 39 wastewater treatment plants and compared to other disease metrics for the city of Houston, TX. We show that wastewater levels are strongly correlated with positivity rate, syndromic surveillance rates of COVID-19 visits, and COVID-19-related general bed use rates at hospitals. We show that the relative timing of wastewater relative to each indicator shifted across the pandemic, likely due to a multitude of factors including testing availability, health-seeking behavior, and changes in viral variants. Next, we show that individual WWTPs led city-wide changes in SARS-CoV-2 viral loads, indicating a distributed monitoring system could be used to enhance the early-warning capability of a wastewater monitoring system. Finally, we describe how the results were used in real-time to inform public health response and resource allocation.

Calibration of Methods for SARS-CoV-2 Environmental Surveillance: A Case Study from Northwest Tuscany

The current pandemic has provided an opportunity to test wastewater-based epidemiology (WBE) as a complementary method to SARS-CoV-2 monitoring in the community. However, WBE infection estimates can be affected by uncertainty factors, such as heterogeneity in analytical procedure, wastewater volume, and population size. In this paper, raw sewage SARS-CoV-2 samples were collected from four wastewater treatment plants (WWTPs) in Tuscany (Northwest Italy) between February and December 2021. During the surveillance period, viral concentration was based on polyethylene glycol (PEG), but its precipitation method was modified from biphasic separation to centrifugation. Therefore, in parallel, the recovery efficiency of each method was evaluated at lab-scale, using two spiking viruses (human coronavirus 229E and mengovirus vMC₀). SARS-CoV-2 genome was found in 80 (46.5%) of the 172 examined samples. Lab-scale experiments revealed that PEG precipitation using centrifugation had the best recovery efficiency (up to 30%). Viral SARS-CoV-2 load obtained from sewage data, adjusted by analytical method and normalized by population of each WWTP, showed a good association with the clinical data in the study area. This study highlights that environmental surveillance data need to be carefully analyzed before their use in the WBE, also considering the sensibility of the analytical methods.

Wild type and variants of SARS-COV-2 in Parisian sewage: presence in raw water and through processes in wastewater treatment plants

The presence of SARS-CoV-2 RNA has been extensively reported at the influent of wastewater treatment plants (WWTPs) worldwide, and its monitoring has been proposed as a potential surveillance tool to early alert of epidemic outbreaks. However, the fate of the SARS-CoV-2 RNA in the treatment process of WWTP has not been widely studied yet; therefore, in this study, we aimed to evaluate the efficiency of treatment processes in reducing SARS-CoV-2 RNA levels in wastewater. The treatment process of three WWTPs of the Parisian area in France was monitored on six different weeks over a period of 2 months (from April 14 to June 9, 2021). SARS-CoV-2 RNA copies were detected using digital polymerase chain reaction (dPCR). Investigation on the presence of variants of concern (Del69-70, E484K, and L452R) was also performed. Additionally, SARS-CoV-2 RNA loads in the WWTPs influents were expressed as the viral concentration in per population equivalent (PE) and showed a good correlation with French public health indicators (incidence rate). SARS-CoV-2 RNA loads were notably reduced along the water treatment lines of the three WWTPs studied (2.5-3.4 log reduction). Finally, very low SARS-CoV-2 RNA loads were detected in effluents (non-detected in over half of the samples) which indicated that the potential risk of the release of wastewater effluents to the environment is probably insignificant, in the case of WWTPs enabling an efficient biological removal of nitrogen.

Longitudinal SARS-CoV-2 RNA wastewater monitoring across a range of scales correlates with total and regional COVID-19 burden in a well-defined urban population

Wastewater-based epidemiology (WBE) is an emerging surveillance tool that has been used to monitor the ongoing COVID-19 pandemic by tracking SARS-CoV-2 RNA shed into wastewater. WBE was performed to monitor the occurrence and spread of SARS-CoV-2 from three wastewater treatment plants (WWTP) and six neighborhoods in the city of Calgary, Canada (population 1.44 million). A total of 222 WWTP and 192 neighborhood samples were collected from June 2020 to May 2021, encompassing the end of the first-wave (June 2020), the second-wave (November end to December 2020) and the third-wave of the COVID-19 pandemic (mid-April to May 2021). Flow-weighted 24-hour composite samples were processed to extract RNA that was then analyzed for two SARS-CoV-2-specific regions of the nucleocapsid gene, N1 and N2, using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Using this approach SARS-CoV-2 RNA was detected in 98.06% (406/414) of wastewater samples. SARS-CoV-2 RNA abundance was compared to clinically diagnosed COVID-19 cases organized by the three-digit postal code of affected individuals' primary residences, enabling correlation analysis at neighborhood, WWTP and city-wide scales. Strong correlations were observed between N1 & N2 gene signals in wastewater and new daily cases for WWTPs and neighborhoods. Similarly, when flow rates at Calgary's three WWTPs were used to normalize observed concentrations of SARS-CoV-2 RNA and combine them into a city-wide signal, this was strongly correlated with regionally diagnosed COVID-19 cases and clinical test percent positivity rate. Linked census data demonstrated disproportionate SARS-CoV-2 in wastewater from areas of the city with lower socioeconomic status and more racialized communities. WBE across a range of urban scales was demonstrated to be an effective mechanism of COVID-19 surveillance.

Acquired insights from the long-term surveillance of SARS-CoV-2 RNA for COVID-19 monitoring: The case of Monterrey Metropolitan Area (Mexico)

Wastewater-based epidemiology offers a time- and cost-effective way to monitor SARS-CoV-2 spread in communities and therefore represents a complement to clinical testing. WBE applicability has been demonstrated in a number of cases over short-term periods as a method for tracking the prevalence of SARS-CoV-2 and an early-warning tool for predicting outbreaks in the population. This study reports SARS-CoV-2 viral loads from wastewater treatment plants (WWTPs) and hospitals over a 6-month period (June to December 2020). Results show that the overall range of viral load in positive tested samples was between 1.2 × 10³ and 3.5 × 10⁶ gene copies/l, unveiling that secondary-treated wastewaters mirrored the viral load of influents. The interpretation suggests that the viral titers found in three out of four WWTPs were associated to clinical COVID-19 surveillance indicators preceding 2-7 days the rise of reported clinical cases. The median wastewater detection rate of SARS-CoV-2 was one out of 14,300 reported new cases. Preliminary model estimates of prevalence ranged from 0.02 to 4.6% for the studied period. This comprehensive statistical and epidemiological analysis demonstrates that the applied wastewater-based approach to COVID-19 surveillance is in general consistent and feasible, although there is room for improvements.

National Scale Real-Time Surveillance of SARS-CoV-2 Variants Dynamics by Wastewater Monitoring in Israel

In this report, we describe a national-scale monitoring of the SARS-CoV-2 (SC-2) variant dynamics in Israel, using multiple-time sampling of 13 wastewater treatment plants. We used a combination of inclusive and selective quantitative PCR assays that specifically identify variants A19/A20 or B.1.1.7 and tested each sample for the presence and relative viral RNA load of each variant. We show that between December 2020 and March 2021, a complete shift in the SC-2 variant circulation was observed, where the B.1.1.7 replaced the A19 in all examined test points. We further show that the normalized viral load (NVL) values and the average new cases per week reached a peak in January 2021 and then decreased gradually in almost all test points, in parallel with the progression of the national vaccination campaign, during February-March 2021. This study demonstrates the importance of monitoring SC-2 variant by using a combination of inclusive and selective PCR tests on a national scale through wastewater sampling, which is far more amendable for high-throughput monitoring compared with sequencing. This approach may be useful for real-time dynamics surveillance of current and future variants, such as the Omicron (BA.1, BA.2) and other variants.

Factors influencing SARS-CoV-2 RNA concentrations in wastewater up to the sampling stage: A systematic review

Wastewater-based surveillance (WBS) for SARS-CoV-2 RNA is a promising complementary approach to monitor community viral circulation. A myriad of factors, however, can influence RNA concentrations in wastewater, impeding its epidemiological value. This article aims to provide an overview and discussion of factors up to the sampling stage that impact SARS-CoV-2 RNA concentration estimates in wastewater. To this end, a systematic review was performed in three databases (MEDLINE, Web of Science and Embase) and two preprint servers (MedRxiv and BioRxiv). Two authors independently screened and selected articles published between January 1, 2019 and May 4, 2021. A total of 22 eligible articles were included in this systematic review. The following factors up to sampling were identified to have an influence on SARS-CoV-2 RNA concentrations in wastewater and its interpretation: (i) shedding-related factors, including faecal shedding parameters (i.e. shedding pattern, recovery, rate, and load distribution), (ii) population size, (iii) in-sewer factors, including solid particles, organic load, travel time, flow rate, wastewater pH and temperature, and (iv) sampling strategy. In conclusion, factors influencing SARS-CoV-2 RNA concentration estimates in wastewater were identified and research gaps were discussed. The identification of these factors supports the need for further research on WBS for COVID-19.

Wastewater surveillance to infer COVID-19 transmission: A systematic review

Successful detection of SARS-COV-2 in wastewater suggests the potential utility of wastewater-based epidemiology (WBE) for COVID-19 community surveillance. This systematic review aims to assess the performance of wastewater surveillance as early warning system of COVID-19 community transmission. A systematic search was conducted in PubMed, Medline, Embase and the WBE Consortium Registry according to PRISMA guidelines for relevant articles published until 31st July 2021. Relevant data were extracted and summarized. Quality of each paper was assessed using an assessment tool adapted from Bilotta et al.'s tool for environmental science. Of 763 studies identified, 92 studies distributed across 34 countries were shortlisted for qualitative synthesis. A total of 26,197 samples were collected between January 2020 and May 2021 from various locations serving population ranging from 321 to 11,400,000 inhabitants. Overall sample positivity was moderate at 29.2% in all examined settings with the spike (S) gene having maximum rate of positive detections and nucleocapsid (N) gene being the most targeted. Wastewater signals preceded confirmed cases by up to 63 days, with 13 studies reporting sample positivity before the first cases were detected in the community. At least 50 studies reported an association of viral load with community cases. While wastewater surveillance cannot replace large-scale diagnostic testing, it can complement clinical surveillance by providing early signs of potential transmission for more active public health responses. However, more studies using standardized and validated methods are required along with risk analysis and modelling to understand the dynamics of viral outbreaks.

SARS-CoV-2 and other pathogens in municipal wastewater, landfill leachate, and solid waste: A review about virus surveillance, infectivity, and inactivation

This review discusses the techniques available for detecting and inactivating of pathogens in municipal wastewater, landfill leachate, and solid waste. In view of the current COVID-19 pandemic, SARS-CoV-2 is being given special attention, with a thorough examination of all possible transmission pathways linked to the selected waste matrices. Despite the lack of works focused on landfill leachate, a systematic review method, based on cluster analysis, allows to analyze the available papers devoted to sewage sludge and wastewater, allowing to focalize the work on technologies able to detect and treat pathogens. In this work, great attention is also devoted to infectivity and transmission mechanisms of SARS-CoV-2. Moreover, the literature analysis shows that sewage sludge and landfill leachate seem to have a remote chance to act as a virus transmission route (pollution-to-human transmission) due to improper collection and treatment of municipal wastewater and solid waste. However due to the incertitude about virus infectivity, these possibilities cannot be excluded and need further investigation. As a conclusion, this paper shows that additional research is required not only on the coronavirus-specific disinfection, but also the regular surveillance or monitoring of viral loads in sewage sludge, wastewater, and landfill leachate. The disinfection strategies need to be optimized in terms of dosage and potential adverse impacts like antimicrobial resistance, among many other factors. Finally, the presence of SARS-CoV-2 and other pathogenic microorganisms in sewage sludge, wastewater, and landfill leachate can hamper the possibility to ensure safe water and public health in economically marginalized countries and hinder the realization of the United Nations' sustainable development goals (SDGs).

Preparing for COVID-2x: Urban Planning Needs to Regard Urological Wastewater as an Invaluable Communal Public Health Asset and Not as a Burden

Prior to the COVID-19 pandemic, the analysis of urological wastewater had been a matter of academic curiosity and community-wide big-picture studies looking at drug use or the presence of select viruses such as Hepatitis. The COVID-19 pandemic saw systematic testing of urological wastewater emerge as a significant early detection tool for the presence of SARS-CoV-2 in a community. Even though the pandemic still rages in all continents, it is time to consider the post-pandemic world. This paper posits that urban planners should treat urological wastewater as a communal public health asset and that future sewer design should allow for stratified multi-order sampling.

SARS-CoV-2: sewage surveillance as an early warning system and challenges in developing countries

Transmission of novel coronavirus (SARS-CoV-2) in humans happens either through airway exposure to respiratory droplets from an infected patient or by touching the virus contaminated surface or objects (fomites). Presence of SARS-CoV-2 in human feces and its passage to sewage system is an emerging concern for public health. Pieces of evidence of the occurrence of viral RNA in feces and municipal wastewater (sewage) systems have not only warned reinforcing the treatment facilities but also suggest that these systems can be monitored to get epidemiological data for checking trend of COVID-19 infection in the community. This review summarizes the occurrence and persistence of novel coronavirus in sewage with an emphasis on the possible water environment contamination. Monitoring of novel coronavirus (SARS-CoV-2) via sewage-based epidemiology could deliver promising information regarding rate of infection providing a valid and complementary tool for tracking and diagnosing COVID-19 across communities. Tracking the sewage systems could act as an early warning tool for alerting the public health authorities for necessary actions. Given the impracticality of testing every citizen with limited diagnostic resources, it is imperative that sewage-based epidemiology can be tested as an early warning system. The need for the development of robust sampling strategies and subsequent detection methodologies and challenges for developing countries are also discussed.