Detection of SARS-CoV-2 RNA in wastewater and comparison to COVID-19 cases in two sewersheds, North Carolina, USA

Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be useful for monitoring population-wide coronavirus disease 2019 (COVID-19) infections, especially given asymptomatic infections and limitations in diagnostic testing. We aimed to detect SARS-CoV-2 RNA in wastewater and compare viral concentrations to COVID-19 case numbers in the respective counties and sewersheds. Influent 24-hour composite wastewater samples were collected from July to December 2020 from two municipal wastewater treatment plants serving different population sizes in Orange and Chatham Counties in North Carolina. After a concentration step via HA filtration, SARS-CoV-2 RNA was detected and quantified by reverse transcription droplet digital polymerise chain reaction (RT-ddPCR) and quantitative PCR (RT-qPCR), targeting the N1 and N2 nucleocapsid genes. SARS-CoV-2 RNA was detected by RT-ddPCR in 100 % (24/24) and 79 % (19/24) of influent wastewater samples from the larger and smaller plants, respectively. In comparison, viral RNA was detected by RT-qPCR in 41.7 % (10/24) and 8.3 % (2/24) of samples from the larger and smaller plants, respectively. Positivity rates and method agreement further increased for the RT-qPCR assay when samples with positive signals below the limit of detection were counted as positive. The wastewater data from the larger plant generally correlated (square similar to 0.5, p < 0.05) with, and even anticipated, the trends in reported COVID-19 cases, with a notable spike in measured viral RNA preceding a spike in cases when students returned to a college campus in the Orange County sewershed. Correlations were generally higher when using estimates of sewershed-level case data rather than county-level data. This work supports use of wastewater surveillance for tracking COVID-19 disease trends, especially in identifying spikes in cases. Wastewater-based epidemiology can be a valuable resource for tracking disease trends, allocating resources, and evaluating policy in the fight against current and future pandemics.

Prevalence of Non-Polio Enteroviruses in the Sewage of Guangzhou City, China, from 2013 to 2021.

Continuous surveillance of enteroviruses (EVs) in urban domestic sewage can timely reflect the circulation of EVs in the environment and crowds, and play a predictive and early warning role in EV-related diseases. To better understand the long-term epidemiological trends of circulating EVs and EV-related diseases, we conducted a 9-year (2013 to 2021) surveillance study of non-polio EVs (NPEVs) in urban sewage in Guangzhou city, China. After concentrating and isolating the viruses from the sewage samples, NPEVs were detected and molecular typing was performed. Twenty-one different NPEV serotypes were identified. The most isolated EVs were echovirus 11 (E11), followed by coxsackievirus (CV) B5, E6, and CVB3. EV species B prevailed in sewage samples, but variations in the annual frequency of different serotypes were also observed in different seasons, due to spatial and temporal factors. E11 and E6 were detected continuously before 2017, and the number of isolates was relatively stable during the surveillance period. However, after their explosive growth in 2018 and 2019, their numbers suddenly decreased significantly. CVB3 and CVB5 had alternating trends; CVB5 was most frequently detected in 2013 to 2014 and 2017 to 2018, while CVB3 was most frequently detected in 2015 to 2016 and 2020 to 2021. Phylogenetic analysis showed that at least two different transmission chains of CVB3 and CVB5 were prevalent in Guangzhou City. Our results show that in the absence of a comprehensive and systematic EV-related disease surveillance system in China, environmental surveillance is a powerful and effective tool to strengthen and further investigate the invisible transmission of EVs in the population. IMPORTANCE This study surveilled urban sewage samples from north China for 9 years to monitor enteroviruses. Samples were collected, processed, and viral identification and molecular typing were performed. We detected 21 different non-polio enteroviruses (NPEVs) with yearly variations in prevalence and peak seasons. In addition, this study is very important for understanding the epidemiology of EVs during the COVID-19 pandemic, as the detection frequency and serotypes of EVs in sewage changed considerably around 2020. We believe that our study makes a significant contribution to the literature because our results strongly suggest that environmental surveillance is an exceptionally important tool, which can be employed to detect and monitor organisms of public health concern, which would otherwise be missed and under-reported by case-based surveillance systems alone.

The city-wide full-scale interactive application of sewage surveillance programme for assisting real-time COVID-19 pandemic control - A case study in Hong Kong.

The paper discusses the implementation of Hong Kong's tailor-made sewage surveillance programme led by the Government, which has demonstrated how an efficient and well-organized sewage surveillance system can complement conventional epidemiological surveillance to facilitate the planning of intervention strategies and actions for combating COVID-19 pandemic in real-time. This included the setting up of a comprehensive sewerage network-based SARS-CoV-2 virus surveillance programme with 154 stationary sites covering 6 million people (or 80 % of the total population), and employing an intensive monitoring programme to take samples from each stationary site every 2 days. From 1 January to 22 May 2022, the daily confirmed case count started with 17 cases per day on 1 January to a maximum of 76,991 cases on 3 March and dropped to 237 cases on 22 May. During this period, a total of 270 "Restriction-Testing Declaration" (RTD) operations at high-risk residential areas were conducted based on the sewage virus testing results, where over 26,500 confirmed cases were detected with a majority being asymptomatic. In addition, Compulsory Testing Notices (CTN) were issued to residents, and the distribution of Rapid Antigen Test kits was adopted as alternatives to RTD operations in areas of moderate risk. These measures formulated a tiered and cost-effective approach to combat the disease in the local setting. Some ongoing and future enhancement efforts to improve efficacy are discussed from the perspective of wastewater-based epidemiology. Forecast models on case counts based on sewage virus testing results were also developed with R2 of 0.9669-0.9775, which estimated that up to 22 May 2022, around 2,000,000 people (~67 % higher than the total number of 1,200,000 reported to the health authority, due to various constraints or limitations) had potentially contracted the disease, which is believed to be reflecting the real situation occurring in a highly urbanized metropolis like Hong Kong.

SARS-CoV-2 concentration in wastewater consistently predicts trends in COVID-19 case counts by at least two days across multiple WWTP scales.

Wastewater surveillance of SARS-CoV-2 has proven instrumental in mitigating the spread of COVID-19 by providing an economical and equitable approach to disease surveillance. Here, we analyze the correlation of SARS-CoV-2 RNA in influents of seven wastewater plants (WWTPs) across the state of South Carolina with corresponding daily case counts to determine whether underlying characteristics of WWTPs and sewershed populations predict stronger correlations. The populations served by these WWTPs have varying social vulnerability and represent 24% of the South Carolina population. The study spanned 15 months from April 19, 2020, to July 1, 2021, which includes the administration of the first COVID-19 vaccines. SARS-CoV-2 RNA concentrations were measured by either reverse transcription quantitative PCR (RT-qPCR) or droplet digital PCR (RT-ddPCR). Although populations served and average flow rate varied across WWTPs, the strongest correlation was identified for six of the seven WWTPs when daily case counts were lagged two days after the measured SARS-CoV-2 RNA concentration in wastewater. The weakest correlation was found for WWTP 6, which had the lowest ratio of population served to average flow rate, indicating that the SARS-CoV-2 signal was too dilute for a robust correlation. Smoothing daily case counts by a 7-day moving average improved correlation strength between case counts and SARS-CoV-2 RNA concentration in wastewater while dampening the effect of lag-time optimization. Correlation strength between cases and SARS-CoV-2 RNA was compared for cases determined at the ZIP-code and sewershed levels. The strength of correlations using ZIP-code-level versus sewershed-level cases were not statistically different across WWTPs. Results indicate that wastewater surveillance, even without normalization to fecal indicators, is a strong predictor of clinical cases by at least two days, especially when SARS-CoV-2 RNA is measured using RT-ddPCR. Furthermore, the ratio of population served to flow rate may be a useful metric to assess whether a WWTP is suitable for a surveillance program.

Rapid Assessment of SARS-CoV-2 Variant-Associated Mutations in Wastewater Using Real-Time RT-PCR.

Within months of the COVID-19 pandemic being declared on March 20, 2020, novel, more infectious variants of SARS-CoV-2 began to be detected in geospatially distinct regions of the world. With international travel being a lead cause of spread of the disease, the importance of rapidly identifying variants entering a country is critical. In this study, we utilized wastewater-based epidemiology (WBE) to monitor the presence of variants in wastewater generated in managed COVID-19 quarantine facilities for international air passengers entering the United Kingdom. Specifically, we developed multiplex reverse transcription quantitative PCR (RT-qPCR) assays for the identification of defining mutations associated with Beta (K417N), Gamma (K417T), Delta (156/157DEL), and Kappa (E154K) variants which were globally prevalent at the time of sampling (April to July 2021). The assays sporadically detected mutations associated with the Beta, Gamma, and Kappa variants in 0.7%, 2.3%, and 0.4% of all samples, respectively. The Delta variant was identified in 13.3% of samples, with peak detection rates and concentrations observed in May 2021 (24%), concurrent with its emergence in the United Kingdom. The RT-qPCR results correlated well with those from sequencing, suggesting that PCR-based detection is a good predictor for variant presence; although, inadequate probe binding may lead to false positive or negative results. Our findings suggest that WBE coupled with RT-qPCR may be used as a rapid, initial assessment to identify emerging variants at international borders and mass quarantining facilities. IMPORTANCE With the global spread of COVID-19, it is essential to identify emerging variants which may be more harmful or able to escape vaccines rapidly. To date, the gold standard to assess variants circulating in communities has been the sequencing of the S gene or the whole genome of SARS-CoV-2; however, that approach is time-consuming and expensive. In this study, we developed two duplex RT-qPCR assays to detect and quantify defining mutations associated with the Beta, Gamma, Delta, and Kappa variants. The assays were validated using RNA extracts derived from wastewater samples taken at quarantine facilities. The results showed good correlation with the results of sequencing and demonstrated the emergence of the Delta variant in the United Kingdom in May 2021. The assays developed here enable the assessment of variant-specific mutations within 2 h after the RNA extract was generated which is essential for outbreak rapid response.

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.

Long-term SARS-CoV-2 surveillance in the wastewater of Stockholm: What lessons can be learned from the Swedish perspective?

Wastewater-based epidemiology (WBE) can be used to track the spread of SARS-CoV-2 in a population. This study presents the learning outcomes from over two-year long monitoring of SARS-CoV-2 in Stockholm, Sweden. The three main wastewater treatment plants in Stockholm, with a total of six inlets, were monitored from April 2020 until June 2022 (in total 600 samples). This spans five major SARS-CoV-2 waves, where WBE data provided early warning signals for each wave. Further, the measured SARS-CoV-2 content in the wastewater correlated significantly with the level of positive COVID-19 tests (r = 0.86; p << 0.0001) measured by widespread testing of the population. Moreover, as a proof-of-concept, six SARS-CoV-2 variants of concern were monitored using hpPCR assay, demonstrating that variants can be traced through wastewater monitoring. During this long-term surveillance, two sampling protocols, two RNA concentration/extraction methods, two calculation approaches, and normalization to the RNA virus Pepper mild mottle virus (PMMoV) were evaluated. In addition, a study of storage conditions was performed, demonstrating that the decay of viral RNA was significantly reduced upon the addition of glycerol to the wastewater before storage at -80 °C. Our results provide valuable information that can facilitate the incorporation of WBE as a prediction tool for possible future outbreaks of SARS-CoV-2 and preparations for future pandemics.

Detection of SARS-CoV-2 RNA in wastewater and comparison to COVID-19 cases in two sewersheds, North Carolina, USA.

Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be useful for monitoring population-wide coronavirus disease 2019 (COVID-19) infections, especially given asymptomatic infections and limitations in diagnostic testing. We aimed to detect SARS-CoV-2 RNA in wastewater and compare viral concentrations to COVID-19 case numbers in the respective counties and sewersheds. Influent 24-hour composite wastewater samples were collected from July to December 2020 from two municipal wastewater treatment plants serving different population sizes in Orange and Chatham Counties in North Carolina. After a concentration step via HA filtration, SARS-CoV-2 RNA was detected and quantified by reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) and quantitative PCR (RT-qPCR), targeting the N1 and N2 nucleocapsid genes. SARS-CoV-2 RNA was detected by RT-ddPCR in 100 % (24/24) and 79 % (19/24) of influent wastewater samples from the larger and smaller plants, respectively. In comparison, viral RNA was detected by RT-qPCR in 41.7 % (10/24) and 8.3 % (2/24) of samples from the larger and smaller plants, respectively. Positivity rates and method agreement further increased for the RT-qPCR assay when samples with positive signals below the limit of detection were counted as positive. The wastewater data from the larger plant generally correlated (⍴ ~0.5, p < 0.05) with, and even anticipated, the trends in reported COVID-19 cases, with a notable spike in measured viral RNA preceding a spike in cases when students returned to a college campus in the Orange County sewershed. Correlations were generally higher when using estimates of sewershed-level case data rather than county-level data. This work supports use of wastewater surveillance for tracking COVID-19 disease trends, especially in identifying spikes in cases. Wastewater-based epidemiology can be a valuable resource for tracking disease trends, allocating resources, and evaluating policy in the fight against current and future pandemics.

Year-long wastewater monitoring for SARS-CoV-2 signals in combined and separate sanitary sewers.

COVID-19 wastewater-based epidemiology has been performed in catchments of various sizes and sewer types with many short-term studies available and multi-seasonal studies emerging. The objective of this study was to compare weekly observations of SARS-CoV-2 genes in municipal wastewater across multiple seasons for different systems as a factor of sewer type (combined, separate sanitary) and system size. Sampling occurred following the first wave of SARS-CoV-2 cases in the study region (June 2020) and continued through the third wave (May 2021), the period during which clinical testing was widely available and different variants dominated clinical cases. The strongest correlations were observed between wastewater N1 concentrations and the cumulative clinical cases reported in the 2 weeks prior to wastewater sampling, followed by the week prior, new cases, and the week after wastewater sampling. Sewer type and size did not necessarily explain the strength of the correlations, indicating that other non-sewer factors may be impacting the observations. In-system sampling results for the largest system sampled are presented for 1 month. Removing wet weather days from the data sets improved even the flow-normalized correlations for the systems, potentially indicating that interpreting results during wet weather events may be more complicated than simply accounting for dilution. PRACTITIONER POINTS: SARS-CoV-2 in wastewater correlated best with total clinical cases reported in 2 weeks before wastewater sampling at the utility level. Study performed when clinical testing was widespread during the year after the first COVID-19 wave in the region. Sewer type and size did not necessarily explain correlation strength between clinical cases and wastewater-based epidemiology results. Removing wet weather days improved correlations for 3/4 utilities studied, including both separate sanitary and combined sewers.

Real-time allelic assays of SARS-CoV-2 variants to enhance sewage surveillance.

To effectively control the ongoing outbreaks of fast-spreading SARS-CoV-2 variants, there is an urgent need to add rapid variant detection and discrimination methods to the existing sewage surveillance systems established worldwide. We designed eight assays based on allele-specific RT-qPCR for real-time allelic discrimination of eight SARS-CoV-2 variants (Alpha, Beta, Gamma, Delta, Omicron, Lambda, Mu, and Kappa) in sewage. In silico analysis of the designed assays for identifying SARS-CoV-2 variants using more than four million SARS-CoV-2 variant sequences yielded ∼100% specificity and >90% sensitivity. All assays could sensitively discriminate and quantify target variants at levels as low as 10 viral RNA copy/µL with minimal cross-reactivity to the corresponding nontarget genotypes, even for sewage samples containing mixtures of SARS-CoV-2 variants with differential abundances. Integration of this method into the routine sewage surveillance in Hong Kong successfully identified the Beta variant in a community sewage. Complete concordance was observed between the results of viral whole-genome sequencing and those of our novel assays in sewage samples that contained exclusively the Delta variant discharged by a clinically diagnosed COVID-19 patient living in a quarantine hotel. Our assays in this method also provided real-time discrimination of the newly emerging Omicron variant in sewage two days prior to clinical test results in another quarantine hotel in Hong Kong. These novel allelic discrimination assays offer a rapid, sensitive, and specific way for detecting multiple SARS-CoV-2 variants in sewage and can be directly integrated into the existing sewage surveillance systems.

Evaluation of RT-qPCR Primer-Probe Sets to Inform Public Health Interventions Based on COVID-19 Sewage Tests.

Sewage surveillance is increasingly employed as a supplementary tool for COVID-19 control. Experiences learnt from large-scale trials could guide better interpretation of the sewage data for public health interventions. Here, we compared the performance of seven commonly used primer-probe sets in RT-qPCR and evaluated the usefulness in the sewage surveillance program in Hong Kong. All selected primer-probe sets reliably detected SARS-CoV-2 in pure water at 7 copies per µL. Sewage matrix did not influence RT-qPCR determination of SARS-CoV-2 concentrated from a small-volume sewage (30 mL) but introduced inhibitory impacts on a large-volume sewage (920 mL) with a ΔCt of 0.2-10.8. Diagnostic performance evaluation in finding COVID-19 cases showed that N1 was the best single primer-probe set, while the ORF1ab set is not recommended. Sewage surveillance using the N1 set for over 3200 samples effectively caught the outbreak trend and, importantly, had a 56% sensitivity and a 96% specificity in uncovering the signal sources from new cases and/or convalescent patients in the community. Our study paves the way for selecting detection primer-probe sets in wider applications in responding to the COVID-19 pandemic.

Long-term monitoring of SARS-CoV-2 RNA in sewage samples from specific public places and STPs to track COVID-19 spread and identify potential hotspots.

Coronavirus pandemic started in March 2020 and since then has caused millions of deaths worldwide. Wastewater-based epidemiology (WBE) can be used as an epidemiological surveillance tool to track SARS-CoV-2 dissemination and provide warning of COVID-19 outbreaks. Considering that there are public places that could be potential hotspots of infected people that may reflect the local epidemiological situation, the presence of SARS-CoV-2 RNA was analyzed by RT-qPCR for approximately 16 months in sewage samples from five public places located in the metropolitan area of Belo Horizonte, MG, Brazil: the sewage treatment plant of Confins International Airport (AIR), the main interstate bus terminal (BUS), an upscale shopping centre (SHC1), a popular shopping centre (SHC2) and a university institute (UNI). The results were compared to those of the influent sewage of the two main sewage treatment plants of Belo Horizonte (STP1 and STP2). Viral monitoring in the STPs proved to be an useful regional surveillance tool, reflecting the trends of COVID-19 cases. However, the viral concentrations in the samples from the selected public places were generally much lower than those of the municipal STPs, which may be due to the behaviour of the non-infected or asymptomatic people, who are likely to visit these places relatively more than the symptomatic infected ones. Among these places, the AIR samples presented the highest viral concentrations and concentration peaks were observed previously to local outbreaks. Therefore, airport sewage monitoring can provide an indication of the regional epidemiological situation. For the other places, particularly the UNI, the results suggested a greater potential to detect the infection and trace cases especially among employees and regular attendees. Taken together, the results indicate that for a regular and permanent sentinel sewage surveillance the sewage from STPs, AIR and UNI could be monitored.

Association of SARS-CoV-2 presence in sewage with public adherence to precautionary measures and reported COVID-19 prevalence in Tehran.

Compared to the growing body of literature on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection and quantification in sewage, there are limited studies reporting on correlations between the viral loads in sewage and the prevalence of infected patients. The present work is a part of the regular monitoring effort for SARS-CoV-2 in wastewater influents from seven wastewater treatment plants (WWTPs) in Tehran, Iran, starting from late September 2020 until early April 2021. These facilities cover ~64% of the metropolis serving >5000,000 M individuals. The study set out to track the trends in the prevalence of COVID-19 in the community using wastewater based epidemiology (WBE) and to investigate whether these measurements correlate with officially reported infections in the population. Composite sewage samples collected over 16 h were enriched by polyethylene glycol precipitation and the corresponding threshold cycle (Ct) profiles for CDC 'N' and 'ORF1ab' assays were derived through real time RT-qPCR. Monte Carlo simulation model was employed to provide estimates of the disease prevalence in the study area. RNA from SARS-CoV-2 was detectable in 100% ('N' assay) and 81% ('ORF1ab' assay) of totally 91 sewage samples, with viral loads ranging from 40 to 45,000 gene copies/L. The outbreak of COVID-19 positively correlated (R2 = 0.80) with the measured viral load in sewage samples. Furthermore, sewage SARS-CoV-2 RNA loads preceded infections in the population by 1 to 2 days, which were in line with public adherence with and support for government instructions to contain the pandemic. Given the transient presence of human host-restricted infections such as SARS-CoV-2, these results provide evidence for assessment of the effectiveness of coordinated efforts that specifically address public health responses based on wastewater-based disease surveillance against not only COVID-19 but also for future infectious outbreaks.

Comparison of residential dormitory COVID-19 monitoring via weekly saliva testing and sewage monitoring.

Wastewater surveillance has been used as a tool for COVID-19 outbreak detection particularly where there was not capability in place for routine and robust individual testing. Given clinical reports that earlier detection is possible following infection from throat/nasal samples compared to fecal samples for COVID-19 patients, the utility of wastewater testing where robust individual testing is possible is less clear. The objective of this study was to compare the results of weekly required COVID-19 saliva tests to weekly wastewater monitoring for residential buildings (i.e., dormitories) located across three college campuses capturing wastewater from 80 to 441 occupants per sampling location. Sampling occurred during the spring semester of the 2021 academic year which captured the third wave of SARS-CoV-2 cases in the study region. Comparison of the saliva and wastewater testing results indicated that the wastewater SARS-CoV-2 concentrations had a strong linear correlation with the previous week's percentage of positive saliva test results and a weak linear correlation with the saliva testing results surrounding the wastewater sampling (four days before and 3 days after). Given that no correlation was observed between the wastewater and the saliva testing from the following week, the weekly saliva testing captured spikes in COVID-19 cases earlier than the weekly wastewater sampling. Interestingly, the N1 gene was observed in buildings on all campuses, but N2 was observed in wastewater on only one of the campuses. N1 and N2 were also observed in sewer biofilm. The campus-specific challenges associated with implementation of wastewater surveillance are discussed. Overall, these results can help inform design of surveillance for early detection of SARS-CoV-2 in residential settings thereby informing mitigation strategies to slow or prevent the spread of the virus among residents in congregate living.

Community-level SARS-CoV-2 sequence diversity revealed by wastewater sampling.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for causing the COVID-19 pandemic, can be detected in untreated wastewater. Wastewater surveillance of SARS-CoV-2 complements clinical data by offering earlier community-level detection, removing underlying factors such as access to healthcare, sampling asymptomatic patients, and reaching a greater population. Here, we compare 24-hour composite samples from the influents of two different wastewater treatment plants (WWTPs) in South Carolina, USA: Columbia and Rock Hill. The sampling intervals span the months of July 2020 and January 2021, which cover the first and second waves of elevated SARS-CoV-2 transmission and COVID-19 clinical cases in these regions. We identify four signature mutations in the surface glycoprotein (spike) gene that are associated with the following variants of interest or concern, VOI or VOC (listed in parenthesis): S477N (B.1.526, Iota), T478K (B.1.617.2, Delta), D614G (present in all VOC as of May 2021), and H655Y (P.1, Gamma). The N501Y mutation, which is associated with three variants of concern, was identified in samples from July 2020, but not detected in January 2021 samples. Comparison of mutations identified in viral sequence databases such as NCBI Virus and GISAID indicated that wastewater sampling detected mutations that were present in South Carolina, but not reflected in the clinical data deposited into databases.

Droplet digital RT-PCR to detect SARS-CoV-2 signature mutations of variants of concern in wastewater.

Wastewater surveillance has shown to be a valuable and efficient tool to obtain information about the trends of COVID-19 in the community. Since the recent emergence of new variants, associated with increased transmissibility and/or antibody escape (variants of concern), there is an urgent need for methods that enable specific and timely detection and quantification of the occurrence of these variants in the community. In this study, we demonstrate the use of RT-ddPCR on wastewater samples for specific detection of mutation N501Y. This assay enabled simultaneous enumeration of lineage B.1.351 (containing the 501Y mutation) and Wild Type (WT, containing 501N) SARS-CoV-2 RNA. Detection of N501Y was possible in samples with mixtures of WT with low proportions of B.1.351 (0.5%) and could accurately determine the proportion of N501Y and WT in mixtures of SARS-CoV-2 RNA. The application to raw sewage samples from the cities of Amsterdam and Utrecht demonstrated that this method can be applied to wastewater samples. The emergence of N501Y in Amsterdam and Utrecht wastewater aligned with the emergence of B.1.1.7 as causative agent of COVID-19 in the Netherlands, indicating that RT-ddPCR of wastewater samples can be used to monitor the emergence of the N501Y mutation in the community. It also indicates that RT-ddPCR could be used for sensitive and accurate monitoring of current (like K417N, K417T, E484K, L452R) or future mutations present in SARS-CoV-2 variants of concern. Monitoring these mutations can be used to obtain insight in the introduction and spread of VOC and support public health decision-making regarding measures to limit viral spread or allocation of testing or vaccination.

Monitoring SARS-CoV-2 in municipal wastewater to evaluate the success of lockdown measures for controlling COVID-19 in the UK.

SARS-CoV-2 and the resulting COVID-19 pandemic represents one of the greatest recent threats to human health, wellbeing and economic growth. Wastewater-based epidemiology (WBE) of human viruses can be a useful tool for population-scale monitoring of SARS-CoV-2 prevalence and epidemiology to help prevent further spread of the disease, particularly within urban centres. Here, we present a longitudinal analysis (March-July 2020) of SARS-CoV-2 RNA prevalence in sewage across six major urban centres in the UK (total population equivalent 3 million) by q(RT-)PCR and viral genome sequencing. Our results demonstrate that levels of SARS-CoV-2 RNA generally correlated with the abundance of clinical cases recorded within the community in large urban centres, with a marked decline in SARS-CoV-2 RNA abundance following the implementation of lockdown measures. The strength of this association was weaker in areas with lower confirmed COVID-19 case numbers. Further, sequence analysis of SARS-CoV-2 from wastewater suggested that multiple genetically distinct clusters were co-circulating in the local populations covered by our sample sites, and that the genetic variants observed in wastewater reflected similar SNPs observed in contemporaneous samples from cases tested in clinical diagnostic laboratories. We demonstrate how WBE can be used for both community-level detection and tracking of SARS-CoV-2 and other virus' prevalence, and can inform public health policy decisions. Although, greater understanding of the factors that affect SARS-CoV-2 RNA concentration in wastewater are needed for the full integration of WBE data into outbreak surveillance. In conclusion, our results lend support to the use of routine WBE for monitoring of SARS-CoV-2 and other human pathogenic viruses circulating in the population and assessment of the effectiveness of disease control measures.

The first case study of wastewater-based epidemiology of COVID-19 in Hong Kong.

Early detection and surveillance of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) virus are key pre-requisites for the effective control of coronavirus disease (COVID-19). So far, sewage testing has been increasingly employed as an alternative surveillance tool for this disease. However, sampling site characteristics impact the testing results and should be addressed in the early use stage of this emerging tool. In this study, we implemented the sewage testing for SARS-CoV-2 virus across sampling sites with different sewage system characteristics. We first validated a testing method using "positive" samples from a hospital treating COVID-19 patients. This method was used to test 107 sewage samples collected during the third wave of the COVID-19 outbreak in Hong Kong (from June 8 to September 29, 2020), covering sampling sites associated with a COVID-19 hospital, public housing estates, and conventional sewage treatment facilities. The highest viral titer of 1975 copy/mL in sewage was observed in a sample collected from the isolation ward of the COVID-19 hospital. Sewage sampling at individual buildings detected the virus 2 days before the first cases were identified. Sequencing of the detected viral fragment confirmed an identical nucleotide sequence to that of the SARS-CoV-2 isolated from human samples. The virus was also detected in sewage treatment facilities, which serve populations of approximately 40,000 to more than one million people.

Roadmap for Managing SARS-CoV-2 and Other Viruses in the Water Environment for Public Health.

The water sector needs to address viral-related public health issues, because water is a virus carrier, which not only spreads viruses (e.g., via drinking water), but also provides information about the circulation of viruses in the community (e.g., via sewage). It has been widely reported that waterborne viral pathogens are abundant, diverse, complex, and threatening the public health in both developed and developing countries. Meanwhile, there is great potential for viral monitoring that can indicate biosafety, treatment performance and community health. New developments in technology have been rising to meet the emerging challenges over the past decades. Under the current coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the world's attention is directed to the urgent need to tackle the most challenging public health issues related to waterborne viruses. Based on critical analysis of the water viral knowledge progresses and gaps, this article offers a roadmap for managing COVID-19 and other viruses in the water environments for ensuring public health.