The Efficient and Practical virus Identification System with ENhanced Sensitivity for Solids (EPISENS-S): A rapid and cost-effective SARS-CoV-2 RNA detection method for routine wastewater surveillance

Identification of protein biomarkers in wastewater linked to the incidence of COVID-19

Wastewater-based epidemiological (WBE) surveillance is a viable disease surveillance technique capable of monitoring the spread of infectious disease agents in sewershed communities. In addition to detecting viral genomes in wastewater, WBE surveillance can identify other endogenous biomarkers that are significantly elevated and excreted in the saliva, urine, and/or stool of infected individuals. Human protein biomarkers allow the realization of real-time WBE surveillance using highly sensitive biosensors. In this study, we analyzed endogenous protein biomarkers present in wastewater influent through liquid chromatography-tandem mass spectrophotometry and scaffold data-independent acquisition to identify candidate target protein biomarkers for WBE surveillance of SARS-CoV-2. We found that out of the 1382 proteins observed in the wastewater samples, 44 were human proteins associated with infectious diseases. These included immune response substances such as immunoglobulins, cytokine-chemokines, and complements, as well as proteins belonging to antimicrobial and antiviral groups. A significant correlation was observed between the intensity of human infectious disease-related protein biomarkers in wastewater and COVID-19 case numbers. Real-time WBE surveillance using biosensors targeting immune response proteins, such as antibodies or immunoglobulins, in wastewater holds promise for expediting the implementation of relevant policies for the effective prevention of infectious diseases in the near future.

Efficient concentration of viral nucleic acid in wastewater through surfactant releasing and a two-step magnetic bead extraction and purification

Wastewater-based epidemiology (WBE) is a valuable complement to clinical monitoring, allowing for effective surveillance of viral infections in populations, and tracking the presence and the epidemiological dynamics of various infectious pathogens in communities. However, virus loads are usually low-abundant in wastewater, and current virus concentration methods for WBE are laborious and time-consuming with low recovery efficiency. To address these challenges, we have developed a magnetic bead-based semi-automated method involving extraction and purification to directly concentrate viral nucleic acids from sewage within 55 min. Prior to concentration, 0.5 % LDS was introduced to pretreat wastewater to inactivate viruses and release viral nucleic acids from both liquid and solid fractions to improve recovery. Under optimal conditions, the concentration method combined with reverse transcription-quantitative polymerase chain reaction (RT-qPCR) can detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA added exogenously in wastewater as low as 4.9 copies/mL within 2.5 h, with an average recovery rate exceeding 80 %. Testing real sewages proved the applicability of the method to detect multiple viruses in different sewages. Additionally, variants of SARS-CoV-2 were successfully identified by multiplex amplicon sequencing in two samples. In conclusion, the new method could provide a much more efficient way for WBE of pathogenic viruses in various sewages.

Enabling quantitative comparison of wastewater surveillance data across methods through data standardization without method standardization

Wastewater surveillance for COVID-19 and other pathogens has expanded globally. Rapid development and availability of various assays has facilitated swift adoption of wastewater surveillance in localities with diverse requirements. However, it presents challenges in comparing data due to methodological variations. Using surrogates for recovery control to address quantification biases has limitations as the recovery of surrogates and target pathogens often diverges significantly. Using non-spiked field-obtained wastewater samples as reference samples in an inter-lab study, this article proposes a straightforward, inexpensive, and most representative way of measuring relative quantification biases that occurs in analyzing field wastewater samples. Five labs participated in the study, testing five types of assays, resulting in a total of seven methods of lab-assay combinations. Each method quantified the concentration of SARS-CoV-2 and pepper mild mottle virus (PMMoV) RNAs in two types of reference samples. The results showed significant variations in quantification among methods, but the relative quantification biases were consistent across reference samples. This suggests that relative quantification biases measured with the reference samples are contingent on methods rather than wastewater samples, and that the once-determined method-specific factors can be used to correct for quantification biases in routine wastewater surveillance results. Subsequent data standardization was performed on year-long observational data from seven cities, serving as a preliminary validation of the proposed approach. This process demonstrated the potential for quantitative data comparison through the bias correction factors obtained in this inter-lab study.

Estimating the effective reproduction number of COVID-19 from population-wide wastewater data: An application in Kagawa, Japan

Although epidemiological surveillance of COVID-19 has been gradually downgraded globally, the transmission of COVID-19 continues. It is critical to quantify the transmission dynamics of COVID-19 using multiple datasets including wastewater virus concentration data. Herein, we propose a comprehensive method for estimating the effective reproduction number using wastewater data. The wastewater virus concentration data, which were collected twice a week, were analyzed using daily COVID-19 incidence data obtained from Takamatsu, Japan between January 2022 and September 2022. We estimated the shedding load distribution (SLD) as a function of time since the date of infection, using a model employing the delay distribution, which is assumed to follow a gamma distribution, multiplied by a scaling factor. We also examined models that accounted for the temporal smoothness of viral load measurement data. The model that smoothed temporal patterns of viral load was the best fit model (WAIC = 2795.8), which yielded a mean estimated distribution of SLD of 3.46 days (95% CrI: 3.01-3.95 days). Using this SLD, we reconstructed the daily incidence, which enabled computation of the effective reproduction number. Using the best fit posterior draws of parameters directly, or as a prior distribution for subsequent analyses, we first used a model that assumed temporal smoothness of viral load concentrations in wastewater, as well as infection counts by date of infection. In the subsequent approach, we examined models that also incorporated weekly reported case counts as a proxy for weekly incidence reporting. Both approaches enabled estimations of the epidemic curve as well as the effective reproduction number from twice-weekly wastewater viral load data. Adding weekly case count data reduced the uncertainty of the effective reproduction number. We conclude that wastewater data are still a valuable source of information for inferring the transmission dynamics of COVID-19, and that inferential performance is enhanced when those data are combined with weekly incidence data.

Correspondence of SARS-CoV-2 genomic sequences obtained from wastewater samples and COVID-19 patient at long-term care facilities

Wastewater-based epidemiology (WBE) has been in the spotlight because of applicability of early detection of virus outbreak and new variants at the catchment area. However, there has been a notable absence of research directly confirming the association between SARS-CoV-2 in wastewater and patient specimens. In this study, we performed a quantitative and qualitative investigation with a genetic-level comparison of SARS-CoV-2 between COVID-19 patients and SARS-CoV-2 positive wastewater samples at long-term care facilities. Wastewater samples were collected via passive sampling from manholes, and SARS-CoV-2 load in wastewater was determined by qPCR. We performed correlation analysis between SARS-CoV-2 load and COVID-19 case number, which suggested that SARS-CoV-2 was detected from wastewater earlier than ascertainment of COVID-19 case. Six and six RNA samples from COVID-19 positive cases and wastewater, respectively, from two facilities were then applied for amplicon sequencing analysis. Mutation analysis revealed high sequence similarity of SARS-CoV-2 variants between wastewater and patient samples (>99 %). To the best of our knowledge, this is the first study demonstrating that WBE is also effective in predicting predominant SARS-CoV-2 variant at facility-level, which is helpful to develop early-warning system for outbreak occurrence with predominant variant.

Wastewater-based reproduction numbers and projections of COVID-19 cases in three areas in Japan, November 2021 to December 2022

BackgroundWastewater surveillance has expanded globally as a means to monitor spread of infectious diseases. An inherent challenge is substantial noise and bias in wastewater data because of the sampling and quantification process, limiting the applicability of wastewater surveillance as a monitoring tool.AimTo present an analytical framework for capturing the growth trend of circulating infections from wastewater data and conducting scenario analyses to guide policy decisions.MethodsWe developed a mathematical model for translating the observed SARS-CoV-2 viral load in wastewater into effective reproduction numbers. We used an extended Kalman filter to infer underlying transmissions by smoothing out observational noise. We also illustrated the impact of different countermeasures such as expanded vaccinations and non-pharmaceutical interventions on the projected number of cases using three study areas in Japan during 2021-22 as an example.ResultsObserved notified cases were matched with the range of cases estimated by our approach with wastewater data only, across different study areas and virus quantification methods, especially when the disease prevalence was high. Estimated reproduction numbers derived from wastewater data were consistent with notification-based reproduction numbers. Our projections showed that a 10-20% increase in vaccination coverage or a 10% reduction in contact rate may suffice to initiate a declining trend in study areas.ConclusionOur study demonstrates how wastewater data can be used to track reproduction numbers and perform scenario modelling to inform policy decisions. The proposed framework complements conventional clinical surveillance, especially when reliable and timely epidemiological data are not available.

Quantitative analysis of SARS-CoV-2 RNA in wastewater and evaluation of sampling frequency during the downward period of a COVID-19 wave in Japan

Wastewater-based epidemiology (WBE) is a practical approach for detecting the presence of SARS-CoV-2 infections and assessing the epidemic trend of the coronavirus disease 2019 (COVID-19). The purpose of this study was to evaluate the minimum sampling frequency required to properly identify the COVID-19 trend during the downward epidemic period when using a highly sensitive RNA detection method. WBE was conducted using the Efficient and Practical virus Identification System with ENhanced Sensitivity for Solids (EPISENS-S), a highly sensitive SARS-CoV-2 RNA detection method, at nine neighboring wastewater treatment plants (WWTPs). These WWTPs were in the same prefecture in Japan, and they had different sewer types, sampling methods, and sampling frequencies. The overall detection rate of SARS-CoV-2 RNA was 97.8 % during the entire study period when the geometric means of new COVID-19 cases per 100,000 inhabitants were between 3.3 and 7.7 in each WWTP. The maximum SARS-CoV-2 RNA concentration in wastewater was 2.14 × 104 copies/L, which corresponded to pepper mild mottle virus (PMMoV)-normalized concentrations of 6.54 × 10-3. We evaluated the effect of sampling frequencies on the probability of a significant correlation with the number of newly reported COVID-19 cases by hypothetically reducing the sampling frequency in the same dataset. When the wastewater sampling frequency occurred 5, 3, 2, and 1 times per week, these results exhibited significant correlations of 100 % (5/5), 89 % (8/9), 85 % (23/27), and 48 % (13/27), respectively. To achieve significant correlation with a high probability of over 85 %, a minimum sampling frequency of twice per week is required, even if sampling methods and sewer types are different. WBE using the EPISENS-S method and a sampling frequency of more than twice a week can be used to properly monitor COVID-19 wave epidemic trends, even during downward periods.

Tracking the effects of the COVID-19 pandemic on viral gastroenteritis through wastewater-based retrospective analyses

The COVID-19 pandemic possibly disrupted the circulation and seasonality of gastroenteritis viruses (e.g., Norovirus (NoV), Sapovirus (SaV), group A rotavirus (ARoV), and Aichivirus (AiV)). Despite the growing application of wastewater-based epidemiology (WBE), there remains a lack of sufficient investigations into the actual impact of the COVID-19 pandemic on the prevalence of gastroenteritis viruses. In this study, we measured NoV GI and GII, SaV, ARoV, and AiV RNA concentrations in 296 influent wastewater samples collected from three wastewater treatment plants (WWTPs) in Sapporo, Japan between October 28, 2018 and January 12, 2023 using the highly sensitive EPISENS™ method. The detection ratios of SaV and ARoV after May 2020 (SaV: 49.8 % (134/269), ARoV: 57.4 % (151/263)) were significantly lower than those before April 2020 (SaV: 93.9 % (31/33), ARoV: 97.0 % (32/33); SaV: p < 3.5×10-7, ARoV: p < 1.5×10-6). Furthermore, despite comparable detection ratios before (88.5 %, 23/26) and during (66.7 %, 80/120) the COVID-19 pandemic (p = 0.032), the concentrations of NoV GII revealed a significant decrease after the onset of the pandemic (p < 1.5×10-7, Cliff's delta = 0.72). NoV GI RNA were sporadically detected (24.7 %, 8/33) before April 2020 and after May 2020 (6.5 %, 17/263), whereas AiV was consistently (100 %, 33/33) detected from wastewater throughout the study period (95.8 %, 252/263). The WBE results demonstrated the significant influence of COVID-19 countermeasures on the circulation of gastroenteritis viruses, with variations observed in the magnitude of their impact across different types of viruses. These epidemiological findings highlight that the hygiene practices implemented to prevent COVID-19 infections may also be effective for controlling the prevalence of gastroenteritis viruses, providing invaluable insights for public health units and the development of effective disease management guidelines.

Tracking community infection dynamics of COVID-19 by monitoring SARS-CoV-2 RNA in wastewater, counting positive reactions by qPCR

Wastewater-based epidemiology has proved useful for monitoring the COVID-19 infection dynamics in communities. However, in regions of low prevalence, low concentrations of SARS-CoV-2 RNA in wastewater make this difficult. Here, we used real-time reverse-transcription PCR (RT-qPCR) to monitor SARS-CoV-2 RNA in wastewater from October 2020 to December 2022 during the third, fourth, fifth, sixth, seventh, and eighth waves of the COVID-19 outbreak in Japan. Viral RNA was below the limit of detection in all samples during the third and fourth waves. However, by counting the number of positive replicates in qPCR of each sample, we found that the positive ratio to all replicates in wastewater was significantly correlated with the number of clinically confirmed cases by the date of symptom onset during the third, fourth, and fifth waves. Time-step analysis indicated that, for 2 days either side of symptom onset, COVID-19 patients excreted in their feces large amounts of virus that wastewater surveillance could detect. We also demonstrated that the viral genome copy number in wastewater, as estimated from the positive ratio of SARSA-CoV-2 RNA, was correlated with the number of clinically confirmed cases. The positive count method is thus useful for tracing COVID-19 dynamics in regions of low prevalence.

Enhanced detection of mpox virus in wastewater using a pre-amplification approach: A pilot study informing population-level monitoring of low-titer pathogens

A recent outbreak of the mpox virus (MPXV) occurred in non-endemic regions of the world beginning in May 2022. Pathogen surveillance systems faced pressure to quickly establish response protocols, offering an opportunity to employ wastewater-based epidemiology (WBE) for population-level monitoring. The pilot study reported herein aimed to: (i) develop a reliable protocol for MPXV DNA detection in wastewater which would reduce false negative reporting, (ii) test this protocol on wastewater from various regions across the United States, and (iii) conduct a state of the science review of the current literature reporting on experimental methods for MPXV detection using WBE. Twenty-four-hour composite samples of untreated municipal wastewater were collected from the states of New Jersey, Georgia, Illinois, Texas, Arizona, and Washington beginning July 3rd, 2022 through October 16th, 2022 (n = 60). Samples underwent vacuum filtration, DNA extraction from captured solids, MPXV DNA pre-amplification, and qPCR analysis. Of the 60 samples analyzed, a total of eight (13%) tested positive for MPXV in the states of Washington, Texas, New Jersey, and Illinois. The presence of clade IIb MPXV DNA in these samples was confirmed via Sanger sequencing and integration of pre-amplification prior to qPCR decreased the rate of false negative detections by 87% as compared to qPCR analysis alone. Wastewater-derived detections of MPXV were compared to clinical datasets, with 50% of detections occurring as clinical cases were increasing/peaking and 50% occurring as clinical cases waned. Results from the literature review (n = 9 studies) revealed successful strategies for the detection of MPXV DNA in wastewater, however also emphasized a need for further method optimization and standardization. Overall, this work highlights the use of pre-amplification prior to qPCR detection as a means to capture the presence of MPXV DNA in community wastewater and offers guidance for monitoring low-titer pathogens via WBE.

Association of wastewater SARS-CoV-2 load with confirmed COVID-19 cases at a university hospital in Sapporo, Japan during the period from February 2021 to February 2023

Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been used to monitor trends in SARS-CoV-2 prevalence in a community without being influenced by clinical testing resources or healthcare-seeking behaviors. Since the rate of mortality from COVID-19 is higher in elderly patients with comorbidities, it is important to protect hospitalized patients from nosocomial infections caused by SARS-CoV-2. SARS-CoV-2 dissemination within a hospital ward was mostly mediated by healthcare workers (HCWs) and patients. HCWs need to understand the occurrence of COVID-19 and reflect this in their infection control measures. The aim of the present study was to determine the potential of SARS-CoV-2 RNA in wastewater as a leading indicator of confirmed COVID-19 cases at a university hospital. The trend of the geometric mean RNA concentrations in wastewater collected in Sapporo corresponded well with that of the number of newly confirmed COVID-19 cases at Hokkaido University Hospital between February 15, 2021 and February 26, 2023 (Pearson's r = 0.8823, p < 0.0001). Our results showed that monitoring SARS-CoV-2 RNA in municipal wastewater was useful for estimating the number of COVID-19 patients in healthcare facilities in the city.

Reduction of SARS-CoV-2 by biological nutrient removal and disinfection processes in full-scale wastewater treatment plants

Detection of SARS-CoV-2 RNA in wastewater poses people's concerns regarding the potential risk in water bodies receiving wastewater treatment effluent, despite the infectious risk of SARS-CoV-2 in wastewater being speculated to be low. Unlike well-studied nonenveloped viruses, SARS-CoV-2 in wastewater is present abundantly in both solid and liquid fractions of wastewater. Reduction of SARS-CoV-2 in past studies were likely underestimated, as SARS-CoV-2 in influent wastewater were quantified in either solid or liquid fraction only. The objectives of this study were (i) to clarify the reduction in SARS-CoV-2 RNA during biological nutrient removal and disinfection processes in full-scale WWTPs, considering the SARS-CoV-2 present in both solid and liquid fractions of wastewater, and (ii) to evaluate applicability of pepper mild mottle virus (PMMoV) as a performance indicator for reduction of SARS-CoV-2 in WWTPs. Accordingly, large amount of SARS-CoV-2 RNA were partitioned in the solid fraction of influent wastewater for composite sampling than grab sampling. When SARS-CoV-2 RNA in the both solid and liquid fractions were considered, log reduction values (LRVs) of SARS-CoV-2 during step-feed multistage biological nitrogen removal (SM-BNR) and enhanced biological phosphorus removal (EBPR) processes ranged between>2.1-4.4 log and did not differ significantly from those in conventional activated sludge (CAS). The LRVs of SARS-CoV-2 RNA in disinfection processes by ozonation and chlorination did not differ significantly. PMMoV is a promising performance indicator to secure reduction of SARS-CoV-2 in WWTPs, because of its higher persistence in wastewater treatment processes and abundance at a detectable concentration even in the final effluent after disinfection.

Near full-automation of COPMAN using a LabDroid enables high-throughput and sensitive detection of SARS-CoV-2 RNA in wastewater as a leading indicator

Wastewater-based epidemiology (WBE) is a promising tool to efficiently monitor COVID-19 prevalence in a community. For WBE community surveillance, automation of the viral RNA detection process is ideal. In the present study, we achieved near full-automation of a previously established method, COPMAN (COagulation and Proteolysis method using MAgnetic beads for detection of Nucleic acids in wastewater), which was then applied to detect SARS-CoV-2 in wastewater for half a year. The automation line employed the Maholo LabDroid and an automated-pipetting device to achieve a high-throughput sample-processing capability of 576 samples per week. SARS-CoV-2 RNA was quantified with the automated COPMAN using samples collected from two wastewater treatment plants in the Sagami River basin in Japan between 1 November 2021 and 24 May 2022, when the numbers of daily reported COVID-19 cases ranged from 0 to 130.3 per 100,000 inhabitants. The automated COPMAN detected SARS-CoV-2 RNA from 81 out of 132 samples at concentrations of up to 2.8 × 10⁵ copies/L. These concentrations showed direct correlations with subsequently reported clinical cases (5-13 days later), as determined by Pearson's and Spearman's cross-correlation analyses. To compare the results, we also conducted testing with the EPISENS-S (Efficient and Practical virus Identification System with ENhanced Sensitivity for Solids, Ando et al., 2022), a previously reported detection method. SARS-CoV-2 RNA detected with EPISENS-S correlated with clinical cases only when using Spearman's method. Our automated COPMAN was shown to be an efficient method for timely and large-scale monitoring of viral RNA, making WBE more feasible for community surveillance.

Moving forward with COVID-19: Future research prospects of wastewater-based epidemiology methodologies and applications

Wastewater-based epidemiology (WBE) has been demonstrated for its great potential in tracking of coronavirus disease 2019 (COVID-19) transmission among populations despite some inherent methodological limitations. These include non-optimized sampling approaches and analytical methods; stability of viruses in sewer systems; partitioning/retention in biofilms; and the singular and inaccurate back-calculation step to predict the number of infected individuals in the community. Future research is expected to (1) standardize best practices in wastewater sampling, analysis and data reporting protocols for the sensitive and reproducible detection of viruses in wastewater; (2) understand the in-sewer viral stability and partitioning under the impacts of dynamic wastewater flow, properties, chemicals, biofilms and sediments; and (3) achieve smart wastewater surveillance with artificial intelligence and big data models. Further specific research is essential in the monitoring of other viral pathogens with pandemic potential and subcatchment applications to maximize the benefits of WBE beyond COVID-19.

Impact of the COVID-19 pandemic on the prevalence of influenza A and respiratory syncytial viruses elucidated by wastewater-based epidemiology

Since the COVID-19 pandemic, a decrease in the prevalence of Influenza A virus (IAV) and respiratory syncytial virus (RSV) has been suggested by clinical surveillance. However, there may be potential biases in obtaining an accurate overview of infectious diseases in a community. To elucidate the impact of the COVID-19 on the prevalence of IAV and RSV, we quantified IAV and RSV RNA in wastewater collected from three wastewater treatment plants (WWTPs) in Sapporo, Japan, between October 2018 and January 2023, using highly sensitive EPISENS™ method. From October 2018 to April 2020, the IAV M gene concentrations were positively correlated with the confirmed cases in the corresponding area (Spearman's r = 0.61). Subtype-specific HA genes of IAV were also detected, and their concentrations showed trends that were consistent with clinically reported cases. RSV A and B serotypes were also detected in wastewater, and their concentrations were positively correlated with the confirmed clinical cases (Spearman's r = 0.36-0.52). The detection ratios of IAV and RSV in wastewater decreased from 66.7 % (22/33) and 42.4 % (14/33) to 4.56 % (12/263) and 32.7 % (86/263), respectively in the city after the COVID-19 prevalence. The present study demonstrates the potential usefulness of wastewater-based epidemiology combined with the preservation of wastewater (wastewater banking) as a tool for better management of respiratory viral diseases.

Comparison of the methods for isolation and detection of SARS-CoV-2 RNA in municipal wastewater

Introduction

Coronavirus SARS-CoV-2 is a causative agent responsible for the current global pandemic situation known as COVID-19. Clinical manifestations of COVID-19 include a wide range of symptoms from mild (i.e., cough, fever, dyspnea) to severe pneumonia-like respiratory symptoms. SARS-CoV-2 has been demonstrated to be detectable in the stool of COVID-19 patients. Waste-based epidemiology (WBE) has been shown as a promising approach for early detection and monitoring of SARS-CoV-2 in the local population performed via collection, isolation, and detection of viral pathogens from environmental sources.

Methods

In order to select the optimal protocol for monitoring the COVID-19 epidemiological situation in region Turiec, Slovakia, we (1) compared methods for SARS-CoV-2 separation and isolation, including virus precipitation by polyethylene glycol (PEG), virus purification via ultrafiltration (Vivaspin®) and subsequent isolation by NucleoSpin RNA Virus kit (Macherey-Nagel), and direct isolation from wastewater (Zymo Environ Water RNA Kit); (2) evaluated the impact of water freezing on SARS- CoV-2 separation, isolation, and detection; (3) evaluated the role of wastewater filtration on virus stability; and (4) determined appropriate methods including reverse transcription-droplet digital PCR (RT-ddPCR) and real-time quantitative polymerase chain reaction (RT-qPCR) (targeting the same genes, i.e., RdRp and gene E) for quantitative detection of SARS-CoV-2 in wastewater samples.

Results

(1) Usage of Zymo Environ Water RNA Kit provided superior quality of isolated RNA in comparison with both ultracentrifugation and PEG precipitation. (2) Freezing of wastewater samples significantly reduces the RNA yield. (3) Filtering is counterproductive when Zymo Environ Water RNA Kit is used. (4) According to the specificity and sensitivity, the RT-ddPCR outperforms RT-qPCR.

Discussion

The results of our study suggest that WBE is a valuable early warning alert and represents a non-invasive approach to monitor viral pathogens, thus protects public health on a regional and national level. In addition, we have shown that the sensitivity of testing the samples with a nearer detection limit can be improved by selecting the appropriate combination of enrichment, isolation, and detection methods.

Wastewater-based prediction of COVID-19 cases using a highly sensitive SARS-CoV-2 RNA detection method combined with mathematical modeling

Wastewater-based epidemiology (WBE) has the potential to predict COVID-19 cases; however, reliable methods for tracking SARS-CoV-2 RNA concentrations (C_RNA) in wastewater are lacking. In the present study, we developed a highly sensitive method (EPISENS-M) employing adsorption-extraction, followed by one-step RT-Preamp and qPCR. The EPISENS-M allowed SARS-CoV-2 RNA detection from wastewater at 50 % detection rate when newly reported COVID-19 cases exceed 0.69/100,000 inhabitants in a sewer catchment. Using the EPISENS-M, a longitudinal WBE study was conducted between 28 May 2020 and 16 June 2022 in Sapporo City, Japan, revealing a strong correlation (Pearson's r = 0.94) between C_RNA and the newly COVID-19 cases reported by intensive clinical surveillance. Based on this dataset, a mathematical model was developed based on viral shedding dynamics to estimate the newly reported cases using C_RNA data and recent clinical data prior to sampling day. This developed model succeeded in predicting the cumulative number of newly reported cases after 5 days of sampling day within a factor of √2 and 2 with a precision of 36 % (16/44) and 64 % (28/44), respectively. By applying this model framework, another estimation mode was developed without the recent clinical data, which successfully predicted the number of COVID-19 cases for the succeeding 5 days within a factor of √2 and 2 with a precision of 39 % (17/44) and 66 % (29/44), respectively. These results demonstrated that the EPISENS-M method combined with the mathematical model can be a powerful tool for predicting COVID-19 cases, especially in the absence of intensive clinical surveillance.

COPMAN: A novel high-throughput and highly sensitive method to detect viral nucleic acids including SARS-CoV-2 RNA in wastewater

During the coronavirus disease 2019 (COVID-19) pandemic, wastewater-based epidemiology (WBE) attracted attention as an objective and comprehensive indicator of community infection that does not require individual inspection. Although several severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection methods from wastewater have been developed, there are obstacles to their social implementation. In this study, we developed the COPMAN (Coagulation and Proteolysis method using Magnetic beads for detection of Nucleic acids in wastewater), an automatable method that can concentrate and detect multiple types of viruses from a limited volume (∼10 mL) of wastewater. The COPMAN consists of a high basicity polyaluminum chloride (PAC) coagulation process, magnetic bead-based RNA purification, and RT-preamplification, followed by qPCR. A series of enzymes exhibiting a high tolerance to PCR inhibitors derived from wastewater was identified and employed in the molecular detection steps in the COPMAN. We compared the detectability of viral RNA from 10-mL samples of virus-spiked (heat-inactivated SARS-CoV-2 and intact RSV) or unspiked wastewater by the COPMAN and other methods (PEG-qPCR, UF-qPCR, and EPISENS-S). The COPMAN was the most efficient for detecting spiked viruses from wastewater, detecting the highest level of pepper mild mottle virus (PMMoV), a typical intrinsic virus in human stool, from wastewater samples. The COPMAN also successfully detected indigenous SARS-CoV-2 RNA from 12 samples of wastewater at concentrations of 2.2 × 10⁴ to 5.4 × 10⁵ copies/L, during initial stages of an infection wave in the right and the left bank of the Sagami River in Japan (0.65 to 11.45 daily reported cases per 100,000 people). These results indicate that the COPMAN is suitable for detection of multiple pathogens from small volume of wastewater in automated stations.