SARS-CoV-2 RNA surveillance in large to small centralized wastewater treatment plants preceding the third COVID-19 resurgence in Bangkok, Thailand

Environmental Dissemination of SARS-CoV-2: An Analysis Employing Crassphage and Next-Generation Sequencing Protocols

This study aimed to investigate the dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in water samples obtained during the coronavirus disease 2019 pandemic period, employing cross-assembly phage (crAssphage) as a fecal contamination biomarker and next-generation sequencing protocols to characterize SARS-CoV-2 variants. Raw wastewater and surface water (stream and sea) samples were collected for over a month in Rio de Janeiro, Brazil. Ultracentrifugation and negatively charged membrane filtration were employed for viral concentration of the wastewater and surface water samples, respectively. Viruses were detected and quantified by (RT-)qPCR applying TaqMan® system protocols. SARS-CoV-2 RNA signals were detected in 92.5% (37/40) of the wastewater samples and in 31.25% (10/32) of the stream water samples, but not in seawater samples. CrAssphage was detected in 100% of the wastewater samples, 93.75% (30/32) of the stream samples, and in 2/4 of the seawater samples. CrAssphage detection and high concentrations in stream surface waters (median 8.95 log10 gc/L) revealed diffuse contamination by domestic wastewater in a region with high sanitary coverage. The correlations detected between SARS-CoV-2 data and the moving averages of clinical cases per capita over the sampling period were moderate to strong when applying a 13-day offset, regardless of normalization by crAssphage data or not. Sequencing of the receptor-binding domain of the spike protein confirmed the detection of SARS-CoV-2, but did not characterize the circulating variant. On the other hand, the whole genome sequencing protocol identified circulation of the Gamma variant, corroborating the sampling period clinical data.

Wastewater-based epidemiology: deriving a SARS-CoV-2 data validation method to assess data quality and to improve trend recognition

Introduction

Accurate and consistent data play a critical role in enabling health officials to make informed decisions regarding emerging trends in SARS-CoV-2 infections. Alongside traditional indicators such as the 7-day-incidence rate, wastewater-based epidemiology can provide valuable insights into SARS-CoV-2 concentration changes. However, the wastewater compositions and wastewater systems are rather complex. Multiple effects such as precipitation events or industrial discharges might affect the quantification of SARS-CoV-2 concentrations. Hence, analysing data from more than 150 wastewater treatment plants (WWTP) in Germany necessitates an automated and reliable method to evaluate data validity, identify potential extreme events, and, if possible, improve overall data quality.

Methods

We developed a method that first categorises the data quality of WWTPs and corresponding laboratories based on the number of outliers in the reproduction rate as well as the number of implausible inflection points within the SARS-CoV-2 time series. Subsequently, we scrutinised statistical outliers in several standard quality control parameters (QCP) that are routinely collected during the analysis process such as the flow rate, the electrical conductivity, or surrogate viruses like the pepper mild mottle virus. Furthermore, we investigated outliers in the ratio of the analysed gene segments that might indicate laboratory errors. To evaluate the success of our method, we measure the degree of accordance between identified QCP outliers and outliers in the SARS-CoV-2 concentration curves.

Results and discussion

Our analysis reveals that the flow and gene segment ratios are typically best at identifying outliers in the SARS-CoV-2 concentration curve albeit variations across WWTPs and laboratories. The exclusion of datapoints based on QCP plausibility checks predominantly improves data quality. Our derived data quality categories are in good accordance with visual assessments.

Conclusion

Good data quality is crucial for trend recognition, both on the WWTP level and when aggregating data from several WWTPs to regional or national trends. Our model can help to improve data quality in the context of health-related monitoring and can be optimised for each individual WWTP to account for the large diversity among WWTPs.

Wastewater-based epidemiology for COVID-19 surveillance and beyond: A survey

The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding wastewater-based epidemiology for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.

Unveiling the silent information of wastewater-based epidemiology of SARS-CoV-2 at community and sanitary zone levels: experience in Córdoba City, Argentina

The emergence of COVID-19 in 2020 significantly enhanced the application of wastewater monitoring for detecting SARS-CoV-2 circulation within communities. From October 2021 to October 2022, we collected 406 wastewater samples weekly from the Córdoba Central Pipeline Network (BG-WWTP) and six specific sewer manholes from sanitary zones (SZs). Following WHO guidelines, we processed samples and detected SARS-CoV-2 RNA and variants using real-time PCR. Monitoring at the SZ level allowed for the development of a viral activity flow map, pinpointing key areas of SARS-CoV-2 circulation and tracking its temporal spread and variant evolution. Our findings demonstrate that wastewater-based surveillance acts as a sensitive indicator of viral activity, detecting imminent increases in COVID-19 cases before they become evident in clinical data. This study highlights the effectiveness of targeted wastewater monitoring at both municipal and SZ levels in identifying viral hotspots and assessing community-wide circulation. Importantly, the data shows that environmental wastewater studies provide valuable insights into virus presence, independent of clinical COVID-19 case records, and offer a robust tool for adapting to future public health challenges.

A Review of Wastewater-Based Epidemiology for the SARS-CoV-2 Virus in Rural, Remote, and Resource-Constrained Settings Internationally: Insights for Implementation, Research, and Policy for First Nations in Canada

Wastewater-based epidemiology (WBE) is regarded as a support tool for detecting and assessing the prevalence of infectious diseases at a population level. For rural, remote, and resource-constrained communities with little access to other public health monitoring tools, WBE can be a low-cost approach to filling gaps in population health knowledge to inform public health risk assessment and decision-making. This rapid review explores and discusses unique considerations of WBE in key settings, with a focus on the detection of the SARS-CoV-2 virus, which has rapidly expanded WBE infrastructure globally. To frame our understanding of possibilities for WBE with First Nations in Alberta, we address the following questions: What are the unique considerations and challenges for WBE under similar contexts in rural, remote, or resource-constrained settings? What are the resources and expertise required to support WBE? This review identifies several unique considerations for WBE in rural, remote, and resource-constrained communities, including costs, accessibility, operator capacity, wastewater infrastructure, and data mobilization-highlighting the need for equity in WBE. In summary, most resource-constrained communities require additional support from external research and/or governmental bodies to undertake WBE.

Development of a wastewater based infectious disease surveillance research system in South Korea

Wastewater-based epidemiology has been used in pathogen surveillance for microorganisms at the community level. This study was conducted to determine the occurrence and trends of infectious pathogens in sewage from Yongin city and the relationships between these pathogens and the incidence of infectious diseases in the community. From December 2022 to November 2023, we collected inflow water from six wastewater treatment plants in Yongin city twice a month. The analyzed microorganisms included 15 respiratory viruses, 7 pneumonia-causing bacteria, 19 acute diarrhea-causing pathogens, SARS-CoV-2, Zika virus, hepatitis A virus, poliovirus, Mpox, and measles. They were detected through real-time PCR and conventional PCR. The concentrations of 9 pathogens among them were additionally analyzed using quantitative real time PCR. The correlation was confirmed through statistical analysis with the rate of detection for pathogens reported by the Korea Disease Control and Prevention Agency. Influenza A virus, human adenovirus, and human rhinovirus were moderately correlated (rho values of 0.45 to 0.58). Campylobacter spp. and sapovirus were strong correlated (rho values of 0.62, 0.63). Enteropathogenic E. coli, human coronavirus, and norovirus GII were very strong correlated (rho values of 0.86 to 0.92). We were able to identify the prevalence of respiratory viral infections, pneumonia, and acute diarrhea-causing pathogens in the community through wastewater-based epidemiology data. This study will be helpful in establishing a system for future surveillance of infectious diseases present in sewage.

Wastewater-based Epidemiology for COVID-19 Surveillance and Beyond: A Survey

The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding wastewater-based epidemiology for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.

Assessment of crAssphage as a biological variable for SARS-CoV-2 data normalization in wastewater surveillance

AIMS

This study aimed to assess the use of cross-assembled phage (crAssphage) as an endogenous control employing a multivariate normalization analysis and its application as a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) data normalizer.

METHODS AND RESULTS

A total of 188 twelve-hour composite raw sewage samples were obtained from eight wastewater treatment plants (WWTP) during a 1-year monitoring period. Employing the N1 and N2 target regions, SARS-CoV-2 RNA was detected in 94% (177) and 90% (170) of the samples, respectively, with a global median of 5 log10 genomic copies per liter (GC l-1). CrAssphage was detected in 100% of the samples, ranging from 8.29 to 10.43 log10 GC l-1, with a median of 9.46 ± 0.40 log10 GC l-1, presenting both spatial and temporal variabilities.

CONCLUSIONS

Although SARS-CoV-2 data normalization employing crAssphage revealed a correlation with clinical cases occurring during the study period, crAssphage normalization by the flow per capita per day of each WWTP increased this correlation, corroborating the importance of normalizing wastewater surveillance data in disease trend monitoring.

Detection of SARS-CoV-2 and Omicron variant RNA in wastewater samples from Manila, Philippines

Manila, a highly urbanized city, is listed as one of the top cities with the highest recorded number of coronavirus disease 2019 (COVID-19) cases in the Philippines. This study aimed to detect and quantify the RNA of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the Omicron variant in 51 wastewater samples collected from three locations in Manila, namely Estero de Santa Clara, Estero de Pandacan, which are open drainages, and a sewage treatment plant (STP) at De La Salle University-Manila, between July 2022 and February 2023. Using one-step reverse transcription-quantitative polymerase chain reaction, SARS-CoV-2 and Omicron variant RNA were detected in 78 % (40/51; 4.9 ± 0.5 log10 copies/L) and 60 % (24/40; 4.4 ± 0.3 log10 copies/L) of wastewater samples collected from all sampling sites, respectively. SARS-CoV-2 RNA was detected frequently at Estero de Santa Clara (88 %, 15/17); its highest concentration was at the STP (6.3 log10 copies/L). The Omicron variant RNA was present in the samples collected (4.4 ± 0.3 log10 copies/L) from all sampling sites, with the highest concentration at the STP (4.9 log10 copies/L). Regardless of normalization, using concentrations of pepper mild mottle virus RNA, SARS-CoV-2 RNA concentrations exhibited the highest positive correlation with COVID-19 reported cases in Manila 5 days after the clinical report. These findings revealed that wastewater-based epidemiology may aid in identifying and monitoring of the presence of pathogens in open drainages and STPs in the Philippines. This paper provides the first documentation on SARS-CoV-2 and the Omicron variant in wastewater from Manila.

Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic

The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1-2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.

Early warning of statewide COVID-19 Omicron wave by sentineled urbanized sewer network monitoring using digital PCR in a province capital city, of Gujarat, India

Wastewater-based epidemiology (WBE) has been implemented globally. However, there remains confusion about the number and frequency of samples to be collected, as well as which types of treatment systems can provide reliable specific details about the virus prevalence in specific areas or communities, enabling prompt management and intervention measures. More research is necessary to fully comprehend the possibility of deploying sentinel locations in sewer networks in larger geographic areas. The present study introduces the first report on wastewater-based surveillance in Gandhinagar City using digital PCR (d-PCR) as a SARS-Cov-2 quantification tool, which describes the viral load from five pumping stations in Gandhinagar from October 2021 to March 2022. Raw wastewater samples (n = 119) were received and analyzed weekly to detect SARS-CoV-2 RNA, 109 of which were positive for N1 or N2 genes. The monthly variation analysis in viral genome copies depicted the highest concentrations in January 2022 and February 2022 (p < 0.05; Wilcoxon signed rank test) coincided with the Omicron wave, which contributed mainly from Vavol and Jaspur pumping stations. Cross-correlation analysis indicated that WBE from five stations in Gandhinagar, i.e., capital city sewer networks, provided two-week lead times to the citywide and statewide active cases (time-series cross-correlation function [CCF]; 0.666 and 0.648, respectively), mainly from individual contributions of the urbanized Kudasan and Vavol stations (CCF; 0.729 and 0.647, respectively). These findings suggest that sewer pumping stations in urbanized neighborhoods can be used as sentinel sites for statewide clinical surveillance and that WBE surveillance using digital PCR can be an efficient monitoring and management tool.

Molecular detection and characterization of SARS-CoV-2 in wastewater in Thailand during 2020-2022

BACKGROUND

SARS-CoV-2 has been detected in feces of infected individuals and in wastewater in many countries, which indicates that wastewater may be used to monitor contamination of the virus in community. However, information about the presence of SARS-CoV-2 in different types of environmental water and their genetic characterization are still limited. The purpose of this study was to investigate the presence of SARS-CoV-2 contaminating in environmental water in Thailand.

METHODS

We collected 600 water samples from 10 different sampling sites in Chiang Mai city, Thailand twice a month from July 2020 to December 2022. The SARS-CoV-2 RNA was detected by real-time RT-PCR and further amplified for ORF1a and S genes to investigate their genetic relationship to the reference strains by phylogenetic analysis.

RESULTS

SARS-CoV-2 was detected at 0.17% in the wastewater sample collected in the vicinity of fresh market where the outbreak of COVID-19 cases were simultaneously reported. The detected SARS-CoV-2 strain (W323/21) had nucleotide and amino acid sequences identical to SARS-CoV-2 Delta variant. Amino acid sequence alignment of spike protein revealed that the W323/21 strain carried a mutation of D950N as it was demonstrated in Delta variant reference strains.

CONCLUSIONS

The findings indicated that SARS-CoV-2 Delta variant was detected in wastewater in Chiang Mai, Thailand during the outbreak of COVID-19, suggesting a circulation of the virus in environmental water and in the community during the outbreak.

Situational assessment for fecal sludge management in major cities of Pakistan

With enhanced focus on global sanitation, access to toilets at the household level is increasing in developing countries although the provision of sewer networks is not expanding at the same pace. This is resulting in the adaptation of on-site sanitation facilities to contain the fecal sludge. The fecal sludge generated by the on-site sanitation facilities requires emptying, treatment, and safe end-use or disposal. In this study, the sanitation situation and need for fecal sludge management was evaluated in major cities of Pakistan including Karachi (provincial capital), Lahore (provincial capital), and Islamabad (national capital). Primary and secondary data were collected from key informant interviews of the stakeholders, national and international reports, research, and review articles. Infographics on wastewater and fecal sludge from origin to disposal were developed using a shit flow diagram tool and enabling environment was evaluated with a modified service delivery assessment tool. The results indicate that sewerage network coverage exists for 60%, 63%, and 50% of the areas in Karachi, Lahore, and Islamabad respectively. The sewerage network in major cities is old, leaking, and insufficient, thus a limited amount of wastewater reaches the treatment plants. Total wastewater treatment in Karachi and Islamabad is 10% and 9% respectively whereas, in Lahore, there is no infrastructure for the same. The safe sanitation in Lahore (8%) and Islamabad (25%) is coming from on-site sanitation systems with fecal sludge buried safely onsite. National level sanitation programs exist in the country but are limited to reducing open defecation and containments of fecal sludge only. The inclusion of complete fecal sludge management related framework, guidelines, and policies can help achieve the goal of safe sanitation for all.

Comparison of ordinary reverse transcription real-time polymerase chain reaction (qRT-PCR) with a newly developed one-step single-tube nested real-time RT-PCR (OSN-qRT-PCR) for sensitive detection of SARS-CoV-2 in wastewater

Wastewater monitoring has proven to be an important approach to detecting and controlling the development of the SARS-CoV-2 pandemic. Various tests based on reverse transcription real-time PCR (qRT-PCR) have been developed and used for the detection of SARS-CoV-2 in wastewater samples. In this study, we attempted to increase the sensitivity of qRT-PCR by developing a one-step single-tube nested qRT-PCR assay (OSN-qRT-PCR). Two variants were developed, oriented to nucleocapsid phosphoprotein gene (N) and to spike protein gene (S), respectively. The performance of conventional qRT-PCR assays oriented to these genes with two novel OSN-qRT-PCR assays were firstly optimized using wastewater artificially contaminated with two encapsidated RNA mimic systems harboring a portion either N or S gene (ENRM and ESRM, respectively). The assays were coupled to a polyethylene glycol-based RNA precipitation/extraction method and applied to detect SARS-CoV-2 in wastewater samples from four cities in Slovakia. Both novel OSN-qRT-PCR assays demonstrated higher detection rates than the ordinary qRT-PCR counterparts. The virus levels in the analyzed wastewater samples had a high or very high relation with the numbers of clinical cases in the monitored regions. In fact, correlation with a 3-, 4-, or 5-day temporal offset was revealed. The OSN-qRT-PCR assays demonstrated robustness, mainly in samples with low viral loads.

M. AH, Fernandez S, Huang AT, Vatanaprasan P, Jay DJ, Saethang T, Luk-in S, Storer RJ, Ounjai P, Devanga Ragupathi NK, Kanthawee P, Sano D, Furukawa T, Sei K, Leelahavanichkul A, Kanjanabuch T, Hirankarn N, Higgins PG, Kicic A, Singer AC, Chatsuwan T, Trowsdale S, Abe S, McLellan AD, Ishikawa H. COVID-19 monitoring with sparse sampling of sewered and non-sewered wastewater in urban and rural communities

Equitable SARS-CoV-2 surveillance in low-resource communities lacking centralized sewers is critical as wastewater-based epidemiology (WBE) progresses. However, large-scale studies on SARS-CoV-2 detection in wastewater from low-and middle-income countries is limited because of economic and technical reasons. In this study, wastewater samples were collected twice a month from 186 urban and rural subdistricts in nine provinces of Thailand mostly having decentralized and non-sewered sanitation infrastructure and analyzed for SARS-CoV-2 RNA variants using allele-specific RT-qPCR. Wastewater SARS-CoV-2 RNA concentration was used to estimate the real-time incidence and time-varying effective reproduction number (Re). Results showed an increase in SARS-CoV-2 RNA concentrations in wastewater from urban and rural areas 14-20 days earlier than infected individuals were officially reported. It also showed that community/food markets were "hot spots" for infected people. This approach offers an opportunity for early detection of transmission surges, allowing preparedness and potentially mitigating significant outbreaks at both spatial and temporal scales.

Temporal study of wastewater surveillance from September 2020 to March 2021: an estimation of COVID-19 patients in Lahore, Pakistan

The first aim of study was to quantify the viral load in the wastewater samples by RT-qPCR testing in Lahore population to estimate the number of patients affected and predict the next resurgence of COVID-19 wave in the city. The second aim of the study was to determine the hotspot areas of Lahore which remained positive more often for virus with high viral load. In this study, n = 420 sewage samples were collected on an average of two weeks intervals from 30 different sewage water disposal stations (14 sampling events) from Sept 2020 to March 2021. RNA was extracted and quantified by RT-qPCR without concentrating the virus in samples. Number of positive disposal sites (7-93%), viral load from sewage samples (100.296 to 103.034), and estimated patients (660-17,030) ranged from low to high according to the surge and restrain of 2nd and 3rd COVID-19 waves in the country. The viral load and estimated patients were reported high in January 2021 and March 2021 which were similar to the peak of 2nd and 3rd waves in Pakistan. Site 18 (Niaz Baig village DS) showed the highest viral load among all sites. Findings of the present study helped to estimate the number of patients and track the resurgence in COVID-19 waves in Lahore particularly, and in Punjab generally. Furthermore, it emphasizes the role of wastewater-based epidemiology to help policymakers strengthen the quarantine measures along with immunization to overcome enteric viral diseases. Local and national stake holders should work in collaboration to improve the environmental hygiene to control the disease.

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.

Saliva and wastewater surveillance for SARS-CoV-2 during school reopening amid COVID-19 pandemic in Thailand

Objectives

School closure during the coronavirus disease 2019 (COVID-19) pandemic resulted in a negative impact on children. Serial testing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been proposed as a measure for safety school reopening. We aimed to study the usefulness of SARS-CoV-2 surveillance by saliva testing and performing wastewater surveillance for SARS-CoV-2 in a day school in a resource-limited setting.

Methods

We conducted a cluster randomized study to investigate the potential use of saliva antigen testing compared to saliva pooling for nucleic acid detection in a primary school in Thailand from December 2021 to March 2022. Wastewater surveillance in the school was also performed.

Results

A total of 484 participants attended the study. SARS-CoV-2 was detected in two participants from the tests provided by the study (one in the pool nucleic acid test arm, and another in the quantitative antigen test arm). Additional ten participants reported positive results on an additional rapid antigen test (RAT) performed by nasal swab when they had symptoms or household contact. There was no difference among arms in viral detection by intention-to-treat and per protocol analysis (p = 0.304 and 0.894, respectively). We also investigated the feasibility of wastewater surveillance to detect the virus in this setting. However, wastewater surveillance could not detect the virus.

Conclusions

In a low COVID-19 prevalence, serial saliva testing and wastewater surveillance for SARS-CoV-2 rarely detected the virus in a day school setting. Performing RAT on nasal swabs when students, teachers or staff have symptoms or household contact might be more reasonable.

Exploring possible strategies for treating SARS-CoV-2 in sewage wastewater: A review of current research and future directions

The advent of acute respiratory coronavirus disease (COVID-19) is convoyed by the shedding of the virus in stool. Although inhalation from person-to-person and aerosol/droplet transmission are the main modes of SARS-Coronavirus-2 (SARS-CoV-2) transmission, currently available evidence indicates the presence of viral RNA in the sewerage wastewater, which highlights the need for more effective corona virus treatment options. In the existing COVID-19 pandemic, a substantial percentage of cases shed SARS-CoV-2 viral RNA in their faeces. Hence the treating this sewerage wastewater with proper surveillance is essential to contain this deadly pathogen from further transmission. Since, the viral disinfectants will not be very effective on sewerage waste as organic matter, and suspended solids in water can protect viruses that adsorb to these particles. More effective methods and measures are needed to prevent this virus from spreading. This review will explore some potential methods to treat the SARS-CoV-2 infected sewerage wastewater, current research and future directions.

Actionable wastewater surveillance: application to a university residence hall during the transition between Delta and Omicron resurgences of COVID-19

Wastewater surveillance has gained traction during the COVID-19 pandemic as an effective and non-biased means to track community infection. While most surveillance relies on samples collected at municipal wastewater treatment plants, surveillance is more actionable when samples are collected "upstream" where mitigation of transmission is tractable. This report describes the results of wastewater surveillance for SARS-CoV-2 at residence halls on a university campus aimed at preventing outbreak escalation by mitigating community spread. Another goal was to estimate fecal shedding rates of SARS-CoV-2 in a non-clinical setting. Passive sampling devices were deployed in sewer laterals originating from residence halls at a frequency of twice weekly during fall 2021 as the Delta variant of concern continued to circulate across North America. A positive detection as part of routine sampling in late November 2021 triggered daily monitoring and further isolated the signal to a single wing of one residence hall. Detection of SARS-CoV-2 within the wastewater over a period of 3 consecutive days led to a coordinated rapid antigen testing campaign targeting the residence hall occupants and the identification and isolation of infected individuals. With knowledge of the number of individuals testing positive for COVID-19, fecal shedding rates were estimated to range from 3.70 log10 gc ‧ g feces-1 to 5.94 log10 gc ‧ g feces-1. These results reinforce the efficacy of wastewater surveillance as an early indicator of infection in congregate living settings. Detections can trigger public health measures ranging from enhanced communications to targeted coordinated testing and quarantine.

A multistate assessment of population normalization factors for wastewater-based epidemiology of COVID-19

Wastewater-based epidemiology (WBE) has become a valuable tool for monitoring SARS-CoV-2 infection trends throughout the COVID-19 pandemic. Population biomarkers that measure the relative human fecal contribution to normalize SARS-CoV-2 wastewater concentrations are needed for improved analysis and interpretation of community infection trends. The Centers for Disease Control and Prevention National Wastewater Surveillance System (CDC NWSS) recommends using the wastewater flow rate or human fecal indicators as population normalization factors. However, there is no consensus on which normalization factor performs best. In this study, we provided the first multistate assessment of the effects of flow rate and human fecal indicators (crAssphage, F+ Coliphage, and PMMoV) on the correlation of SARS-CoV-2 wastewater concentrations and COVID-19 cases using the CDC NWSS dataset of 182 communities across six U.S. states. Flow normalized SARS-CoV-2 wastewater concentrations produced the strongest correlation with COVID-19 cases. The correlation from the three human fecal indicators were significantly lower than flow rate. Additionally, using reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) significantly improved correlation values over samples that were analyzed with real-time reverse transcription quantitative polymerase chain reaction (rRT-qPCR). Our assessment shows that utilizing flow normalization with RT-ddPCR generate the strongest correlation between SARS-CoV-2 wastewater concentrations and COVID-19 cases.

Occurrence of multiple respiratory viruses in wastewater in Queensland, Australia: Potential for community disease surveillance

The early warning and tracking of COVID-19 prevalence in the community provided by wastewater surveillance has highlighted its potential for much broader viral disease surveillance. In this proof-of-concept study, 46 wastewater samples from four wastewater treatment plants (WWTPs) in Queensland, Australia, were analyzed for the presence and abundance of 13 respiratory viruses, and the results were compared with reported clinical cases. The viruses were concentrated using the adsorption-extraction (AE) method, and extracted nucleic acids were analyzed using qPCR and RT-qPCR. Among the viruses tested, bocavirus (BoV), parechovirus (PeV), rhinovirus A (RhV A) and rhinovirus B (RhV B) were detected in all wastewater samples. All the tested viruses except influenza B virus (IBV) were detected in wastewater sample from at least one WWTP. BoV was detected with the greatest concentration (4.96-7.22 log10 GC/L), followed by Epstein-Barr virus (EBV) (4.08-6.46 log10 GC/L), RhV A (3.95-5.63 log10 GC/L), RhV B (3.74-5.61 log10 GC/L), and PeV (3.17-5.32 log10 GC/L). Influenza viruses and respiratory syncytial virus (RSV) are notifiable conditions in Queensland, allowing the gene copy (GC) concentrations to be compared with reported clinical cases. Significant correlations (ρ = 0.60, p < 0.01 for IAV and ρ = 0.53, p < 0.01 for RSV) were observed when pooled wastewater influenza A virus (IAV) and RSV log10 GC/L concentrations were compared to log10 clinical cases among the four WWTP catchments. The positive predictive value for the presence of IAV and RSV in wastewater was 97 % for both IAV and RSV clinical cases within the four WWTP catchments. The overall accuracy of wastewater analysis for predicting clinical cases of IAV and RSV was 97 and 90 %, respectively. This paper lends credibility to the application of wastewater surveillance to monitor respiratory viruses of various genomic characteristics, with potential uses for increased surveillance capabilities and as a tool in understanding the dynamics of disease circulation in the communities.

Wastewater monitoring in tourist cities as potential sentinel sites for near real-time dynamics of imported SARS-CoV-2 variants

Wastewater-based epidemiology (WBE) complements the clinical surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants' distribution in populations. Many developed nations have established national and regional WBE systems; however, governance and budget constraints could be obstacles for low- and middle-income countries. An urgent need thus exists to identify hotspots to serve as sentinel sites for WBE. We hypothesized that representative wastewater treatment plants (WWTPs) in two international gateway cities, Bangkok and Phuket, Thailand, could be sentineled for SARS-CoV-2 and its variants to reflect the clinical distribution patterns at city level and serve as early indicators of new variants entering the country. Municipal wastewater samples (n = 132) were collected from eight representative municipal WWTPs in Bangkok and Phuket during 19 sampling events from October 2021 to March 2022, which were tested by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) using the US CDC N1 and N2 multiplex and variant (Alpha, Delta, and Omicron BA.1 and BA.2) singleplex assays. The variant detection ratios from Bangkok and Phuket followed similar trends to the national clinical testing data, and each variant's viral loads agreed with the daily new cases (3-d moving average). Omicron BA.1 was detected in Phuket wastewater prior to Bangkok, possibly due to Phuket's WWTPs serving tourist communities. We found that the Omicron BA.1 and BA.2 viral loads predominantly drove the SARS-CoV-2 resurgence. We also noted a shifting pattern in the Bangkok WBE from a 22-d early warning in early 2021 to a near real-time pattern in late 2021. The potential application of tourist hotspots for WBE to indicate the arrival of new variants and re-emerging or unprecedented infectious agents could support tourism-dependent economies by complementing the reduced clinical regulations while maintaining public health protection via wastewater surveillance.

Regional and temporal differences in the relation between SARS-CoV-2 biomarkers in wastewater and estimated infection prevalence - Insights from long-term surveillance

Wastewater-based epidemiology provides a conceptual framework for the evaluation of the prevalence of public health related biomarkers. In the context of the Coronavirus disease-2019, wastewater monitoring emerged as a complementary tool for epidemic management. In this study, we evaluated data from six wastewater treatment plants in the region of Saxony, Germany. The study period lasted from February to December 2021 and covered the third and fourth regional epidemic waves. We collected 1065 daily composite samples and analyzed SARS-CoV-2 RNA concentrations using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Regression models quantify the relation between RNA concentrations and disease prevalence. We demonstrated that the relation is site and time specific. Median loads per diagnosed case differed by a factor of 3-4 among sites during both waves and were on average 45 % higher during the third wave. In most cases, log-log-transformed data achieved better regression performance than non-transformed data and local calibration outperformed global models for all sites. The inclusion of lag/lead time, discharge and detection probability improved model performance in all cases significantly, but the importance of these components was also site and time specific. In all cases, models with lag/lead time and log-log-transformed data obtained satisfactory goodness-of-fit with adjusted coefficients of determination higher than 0.5. Back-estimation of testing efficiency from wastewater data confirmed state-wide prevalence estimation from individual testing statistics, but revealed pronounced differences throughout the epidemic waves and among the different sites.

Retrospective Analysis of Wastewater-Based Epidemiology of SARS-CoV-2 in Residences on a Large College Campus: Relationships between Wastewater Outcomes and COVID-19 Cases across Two Semesters with Different COVID-19 Mitigation Policies

Wastewater-based epidemiology (WBE) has been utilized for outbreak monitoring and response efforts in university settings during the coronavirus disease 2019 (COVID-19) pandemic. However, few studies examined the impact of university policies on the effectiveness of WBE to identify cases and mitigate transmission. The objective of this study was to retrospectively assess relationships between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) wastewater outcomes and COVID-19 cases in residential buildings of a large university campus across two academic semesters (August 2020-May 2021) under different COVID-19 mitigation policies. Clinical case surveillance data of student residents were obtained from the university COVID-19 response program. We collected and processed building-level wastewater for detection and quantification of SARS-CoV-2 RNA by RT-qPCR. The odds of obtaining a positive wastewater sample increased with COVID-19 clinical cases in the fall semester (OR = 1.50, P value = 0.02), with higher odds in the spring semester (OR = 2.63, P value < 0.0001). We observed linear associations between SARS-CoV-2 wastewater concentrations and COVID-19 clinical cases (parameter estimate = 1.2, P value = 0.006). Our study demonstrated the effectiveness of WBE in the university setting, though it may be limited under different COVID-19 mitigation policies. As a complementary surveillance tool, WBE should be accompanied by robust administrative and clinical testing efforts for the COVID-19 pandemic response.

Temporal Variation of SARS-CoV-2 Levels in Wastewater from a Meat Processing Plant

Wastewater-based surveillance (WBS) on SARS-CoV-2 has been proved to be an effective approach to estimate the prevalence of COVID-19 in communities and cities. However, its application was overlooked at smaller scale, such as a single facility. Meat processing plants are hotspots for COVID-19 outbreaks due to their unique environment that are favorable for the survival and persistence of SARS-CoV-2. This is the first known WBS study in meat processing plants. The goal was to understand the temporal variation of the SARS-CoV-2 levels in wastewater from a meat processing plant in Canada during a three-month campaign and to find any correlation with clinically confirmed cases in the surrounding city area. Higher SARS-CoV-2 concentrations and detection frequencies were observed in the solid fraction compared to the liquid fraction of the wastewater. The viruses can be preserved in the solid fraction of wastewater for up to 12 days. The wastewater virus level did not correlate to the city-wide COVID-19 cases due to the unmatching scales. WBS on SARS-CoV-2 in meat processing plants can be useful for identifying COVID-19 outbreaks in the facility and serve as an effective alternative when resources for routine individual testing are not available.

Correlation between SARS-CoV-2 RNA concentration in wastewater and COVID-19 cases in community: A systematic review and meta-analysis

Wastewater-based epidemiology (WBE) has been considered as a promising approach for population-wide surveillance of coronavirus disease 2019 (COVID-19). Many studies have successfully quantified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentration in wastewater (CRNA). However, the correlation between the CRNA and the COVID-19 clinically confirmed cases in the corresponding wastewater catchments varies and the impacts of environmental and other factors remain unclear. A systematic review and meta-analysis were conducted to identify the correlation between CRNA and various types of clinically confirmed case numbers, including prevalence and incidence rates. The impacts of environmental factors, WBE sampling design, and epidemiological conditions on the correlation were assessed for the same datasets. The systematic review identified 133 correlation coefficients, ranging from -0.38 to 0.99. The correlation between CRNA and new cases (either daily new, weekly new, or future cases) was stronger than that of active cases and cumulative cases. These correlation coefficients were potentially affected by environmental and epidemiological conditions and WBE sampling design. Larger variations of air temperature and clinical testing coverage, and the increase of catchment size showed strong negative impacts on the correlation between CRNA and COVID-19 case numbers. Interestingly, the sampling technique had negligible impact although increasing the sampling frequency improved the correlation. These findings highlight the importance of viral shedding dynamics, in-sewer decay, WBE sampling design and clinical testing on the accurate back-estimation of COVID-19 case numbers through the WBE approach.

Application of neighborhood-scale wastewater-based epidemiology in low COVID-19 incidence situations

Wastewater-based epidemiology (WBE), an emerging approach for community-wide COVID-19 surveillance, was primarily characterized at large sewersheds such as wastewater treatment plants serving a large population. Although informed public health measures can be better implemented for a small population, WBE for neighborhood-scale sewersheds is less studied and not fully understood. This study applied WBE to seven neighborhood-scale sewersheds (average population of 1471) from January to November 2021. Community testing data showed an average of 0.004 % incidence rate in these sewersheds (97 % of monitoring periods reported two or fewer daily infections). In 92 % of sewage samples, SARS-CoV-2 N gene fragments were below the limit of quantification. We statistically determined 10-2.6 as the threshold of the SARS-CoV-2 N gene concentration normalized to pepper mild mottle virus (N/PMMOV) to alert high COVID-19 incidence rate in the studied sewershed. This threshold of N/PMMOV identified neighborhood-scale outbreaks (COVID-19 incidence rate higher than 0.2 %) with 82 % sensitivity and 51 % specificity. Importantly, neighborhood-scale WBE can discern local outbreaks that would not otherwise be identified by city-scale WBE. Our findings suggest that neighborhood-scale WBE is an effective community-wide disease surveillance tool when COVID-19 incidence is maintained at a low level.

Wastewater-Based Epidemiology for SARS-CoV-2 Biomarkers: Evaluation of Normalization Methods in Small and Large Communities in Southern Germany

In the context of the COVID-19 pandemic, wastewater-based epidemiology (WBE) emerged as a useful tool to account for the prevalence of SARS-CoV-2 infections on a population scale. In this study, we analyzed wastewater samples from three large (>300,000 people served) and four small (<25,000 people served) communities throughout southern Germany from August to December 2021, capturing the fourth infection wave in Germany dominated by the Delta variant (B.1.617.2). As dilution can skew the SARS-CoV-2 biomarker concentrations in wastewater, normalization to wastewater parameters can improve the relationship between SARS-CoV-2 biomarker data and clinical prevalence data. In this study, we investigated the suitability and performance of various normalization parameters. Influent flow data showed strong relationships to precipitation data; accordingly, flow-normalization reacted distinctly to precipitation events. Normalization by surrogate viruses CrAssphage and pepper mild mottle virus showed varying performance for different sampling sites. The best normalization performance was achieved with a mixed fecal indicator calculated from both surrogate viruses. Analyzing the temporal and spatial variation of normalization parameters proved to be useful to explain normalization performance. Overall, our findings indicate that the performance of surrogate viruses, flow, and hydro-chemical data is site-specific. We recommend testing the suitability of normalization parameters individually for specific sewage systems.

Comparative genomic analyses of pathogenic bacteria and viruses and antimicrobial resistance genes in an urban transportation canal

Water commuting is a major urban transportation method in Thailand. However, urban boat commuters risk exposure to microbially contaminated bioaerosols or splash. We aimed to investigate the microbial community structures, identify bacterial and viral pathogens, and assess the abundance of antimicrobial resistance genes (ARGs) using next-generation sequencing (NGS) at 10 sampling sites along an 18 km transportation boat route in the Saen Saep Canal, which traverses cultural, commercial, and suburban land-based zones. The shotgun metagenomic (Illumina HiSeq) and 16S rRNA gene amplicon (V4 region) (Illumina MiSeq) sequencing platforms revealed diverse microbial clusters aligned with the zones, with explicit segregation between the cultural and suburban sites. The shotgun metagenomic sequencing further identified bacterial and viral pathogens, and ARGs. The predominant bacterial pathogens (>0.5 % relative abundance) were the Burkholderia cepacia complex, Arcobacter butzleri, Burkholderia vietnamiensis, Klebsiella pneumoniae, and the Enterobacter cloacae complex. The viruses (0.28 %-0.67 % abundance in all microbial sequences) comprised mainly vertebrate viruses and bacteriophages, with encephalomyocarditis virus (33.3 %-58.2 % abundance in viral sequences), hepatitis C virus genotype 1, human alphaherpesvirus 1, and human betaherpesvirus 6A among the human viral pathogens. The 15 ARG types contained 611 ARG subtypes, including those resistant to beta-lactam, which was the most diverse and abundant group (206 subtypes; 17.0 %-27.5 %), aminoglycoside (94 subtypes; 9.6 %-15.3 %), tetracycline (80 subtypes; 15.6 %-20.2 %), and macrolide (79 subtypes; 14.5 %-32.1 %). Interestingly, the abundance of ARGs associated with resistance to beta-lactam, trimethoprim, and sulphonamide, as well as A. butzleri and crAssphage, at the cultural sites was significantly different from the other sites (p < 0.05). We demonstrated the benefits of using NGS to deliver insights into microbial communities, and antimicrobial resistance, both of which pose a risk to human health. Using NGS may facilitate microbial risk mitigation and management for urban water commuters and proximal residents.

A critical review on the existing wastewater treatment methods in the COVID-19 era: What is the potential of advanced oxidation processes in combatting viral especially SARS-CoV-2?

The COVID-19 epidemic has put the risk of virus contamination in water bodies on the horizon of health authorities. Hence, finding effective ways to remove the virus, especially SARS-CoV-2, from wastewater treatment plants (WWTPs) has emerged as a hot issue in the last few years. Herein, this study first deals with the fate of SARS-CoV-2 genetic material in WWTPs, then critically reviews and compares different wastewater treatment methods for combatting COVID-19 as well as to increase the water quality. This critical review sheds light the efficiency of advanced oxidation processes (AOPs) to inactivate virus, specially SARS-CoV-2 RNA. Although several physicochemical treatment processes (e.g. activated sludge) are commonly used to eliminate pathogens, AOPs are the most versatile and effective virus inactivation methods. For instance, TiO2 is the most known and widely studied photo-catalyst innocuously utilized to degrade pollutants as well as to photo-induce bacterial and virus disinfection due to its high chemical resistance and efficient photo-activity. When ozone is dissolved in water and wastewater, it generates a wide spectrum of the reactive oxygen species (ROS), which are responsible to degrade materials in virus membranes resulting in destroying the cell wall. Furthermore, electrochemical advanced oxidation processes act through direct oxidation when pathogens react at the anode surface or by indirect oxidation through oxidizing species produced in the bulk solution. Consequently, they represent a feasible choice for the inactivation of a wide range of pathogens. Nonetheless, there are some challenges with AOPs which should be addressed for application at industrial-scale.

Useful molecular tools for facing next pandemic events: Effective sample preparation and improved RT-PCR for highly sensitive detection of SARS-CoV-2 in wastewater environment

Viral pandemics can be inevitable in the next future. Considering SARS-CoV-2 pandemics as an example, there seems to be a need to develop a surveillance system able to monitor the presence of potential pathogenic agents. The sewage and wastewater environments demonstrated to be suitable targets for such kind of analysis. In addition, it is important to have reliable molecular diagnostic tools and also to develop a robust detection strategy. In this study, an effective sample preparation procedure was selected from four options and combined with a newly developed improved RT-PCR. First, a model viral system was constructed, containing a fragment of the SARS-CoV-2 gene encoding for the Spike protein. The encapsidated S RNA mimic (ESRM) was based on the plum pox virus (PPV) genome with the inserted targeted gene fragment. ESRM was used for seeding wastewater samples in order to evaluate the viral recovery of four different viral RNA concentration/extraction methods. The efficiency of individual approaches was assessed by the use of a quantitative reverse transcription PCR (qRT-PCR) and by a one-step single-tube nested quantitative reverse transcription PCR (OSN-qRT-PCR). For the detection of viruses in wastewater samples with low viral loads, OSN-qRT-PCR assay produced the most satisfactory results and the highest sensitivity.

Artificial neural network-based estimation of COVID-19 case numbers and effective reproduction rate using wastewater-based epidemiology

As a cost-effective and objective population-wide surveillance tool, wastewater-based epidemiology (WBE) has been widely implemented worldwide to monitor the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentration in wastewater. However, viral concentrations or loads in wastewater often correlate poorly with clinical case numbers. To date, there is no reliable method to back-estimate the coronavirus disease 2019 (COVID-19) case numbers from SARS-CoV-2 concentrations in wastewater. This greatly limits WBE in achieving its full potential in monitoring the unfolding pandemic. The exponentially growing SARS-CoV-2 WBE dataset, on the other hand, offers an opportunity to develop data-driven models for the estimation of COVID-19 case numbers (both incidence and prevalence) and transmission dynamics (effective reproduction rate). This study developed artificial neural network (ANN) models by innovatively expanding a conventional WBE dataset to include catchment, weather, clinical testing coverage and vaccination rate. The ANN models were trained and evaluated with a comprehensive state-wide wastewater monitoring dataset from Utah, USA during May 2020 to December 2021. In diverse sewer catchments, ANN models were found to accurately estimate the COVID-19 prevalence and incidence rates, with excellent precision for prevalence rates. Also, an ANN model was developed to estimate the effective reproduction number from both wastewater data and other pertinent factors affecting viral transmission and pandemic dynamics. The established ANN model was successfully validated for its transferability to other states or countries using the WBE dataset from Wisconsin, USA.

Risk Assessment and Prevention Strategy of Virus Infection in the Context of University Resumption

The risk assessment system of virus infection probability and the prevention measures for virus transmission are keys to controlling epidemics. In the context of university resumption, this study identifies the risk elements in terms of the mechanism of virus transmission. The effect of two recognized effective measures, i.e., occupancy constraints and ventilation intervention, on the infection risk are quantified and compared using the improved Wells–Riley model. Considering the priority of these two measures, the controlling quantity are determined, and the optimal schemes are proposed based on the targeted infection risk. The results show that the effect of reducing infection risk by constraining occupancy within 25% of all public campus buildings is better than that achieved by increasing the ventilation rate alone. If the ventilation system of the building type is operated by occupiers, it is a priority to prevent the risk of virus infection by restricting occupancy and ensuring the distance between occupants, while if the ventilation system of the building type is centrally controlled, it is a priority to increase the ventilation rate and then limit the occupancy rate during peak periods to 75%.

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.

Persistence of Tilapia tilapinevirus in fish rearing and environmental water and its ability to infect cell line

Tilapia tilapinevirus, or Tilapia Lake Virus (TiLV), is a RNA virus associated with mass morbidity and mortality in tilapia, leading to severe economic losses for global tilapia aquaculture. In this study, we investigated the persistence of TiLV in water by spiking sterile distilled water (SDW), freshwater collected from rearing fish tanks (FW) and natural pond water (PW) at 27°C as a representative of environmental water conditions with 0.6 ml of stock virus (3.18 × 10⁷ viral copies/ml of water). The water samples were filtered through an electronegative charge membrane and quantified using reverse transcriptase quantitative PCR at 0, 3, 5, 7, 10 and 14 days post-inoculation. The results revealed that TiLV RNA in SDW was reduced by 1.34 log₁₀ in 14 days. A similar approximately 4 log₁₀ removal of the virus in FW and PW was observed at 3 and 7 days, respectively. Moreover, the infectivity of TiLV was further studied; the virus lost its infectivity in E-11 cells after 1 day in SDW, FW and PW water samples, even though the virus was spiked 10 more times than in the viral persistence study. Taken together, the results could be applied to improving biosecurity practices in tilapia farms by disinfecting or resting reservoir water for at least three to five days prior to stocking tilapia, to limit the spread of TiLV.

Evaluation of process limit of detection and quantification variation of SARS-CoV-2 RT-qPCR and RT-dPCR assays for wastewater surveillance

Effective wastewater surveillance of SARS-CoV-2 RNA requires the rigorous characterization of the limit of detection resulting from the entire sampling process - the process limit of detection (PLOD). Yet to date, no studies have gone beyond quantifying the assay limit of detection (ALOD) for RT-qPCR or RT-dPCR assays. While the ALOD is the lowest number of gene copies (GC) associated with a 95% probability of detection in a single PCR reaction, the PLOD represents the sensitivity of the method after considering the efficiency of all processing steps (e.g., sample handling, concentration, nucleic acid extraction, and PCR assays) to determine the number of GC in the wastewater sample matrix with a specific probability of detection. The primary objective of this study was to estimate the PLOD resulting from the combination of primary concentration and extraction with six SARS-CoV-2 assays: five RT-qPCR assays (US CDC N1 and N2, China CDC N and ORF1ab (CCDC N and CCDC ORF1ab), and E_Sarbeco RT-qPCR, and one RT-dPCR assay (US CDC N1 RT-dPCR) using two models (exponential survival and cumulative Gaussian). An adsorption extraction (AE) concentration method (i.e., virus adsorption on membrane and the RNA extraction from the membrane) was used to concentrate gamma-irradiated SARS-CoV-2 seeded into 36 wastewater samples. Overall, the US CDC N1 RT-dPCR and RT-qPCR assays had the lowest ALODs (< 10 GC/reaction) and PLODs (<3,954 GC/50 mL; 95% probability of detection) regardless of the seeding level and model used. Nevertheless, consistent amplification and detection rates decreased when seeding levels were < 2.32 × 103 GC/50 mL even for US CDC N1 RT-qPCR and RT-dPCR assays. Consequently, when SARS-CoV-2 RNA concentrations are expected to be low, it may be necessary to improve the positive detection rates of wastewater surveillance by analyzing additional field and RT-PCR replicates. To the best of our knowledge, this is the first study to assess the SARS-CoV-2 PLOD for wastewater and provides important insights on the analytical limitations for trace detection of SARS-CoV-2 RNA in wastewater.