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.

Targeted amplicon sequencing of wastewater samples for detecting SARS-CoV-2 variants with high sensitivity and resolution.

Wastewater-based epidemiology (WBE) is a promising approach for monitoring the spread of SARS-CoV-2 within communities. Although qPCR-based WBE is powerful in that it allows quick and highly sensitive detection of this virus, it can provide limited information about which variants are responsible for the overall increase or decrease of this virus in sewage, and this hinders accurate risk assessments. To resolve this problem, we developed a next generation sequencing (NGS)-based method to determine the identity and composition of individual SARS-CoV-2 variants in wastewater samples. Combination and optimization of targeted amplicon-sequencing and nested PCR allowed detection of each variant with sensitivity comparable to that of qPCR. In addition, by targeting the receptor binding domain (RBD) of the S protein, which has mutations informative for variant classification, we could discriminate most variants of concern (VOC) and even sublineages of Omicron (BA.1, BA.2, BA.4/5, BA.2.75, BQ.1.1 and XBB.1). Focusing on a limited domain has a benefit of decreasing the sequencing reads. We applied this method to wastewater samples collected from a wastewater treatment plant in Kyoto city throughout 13 months (from January 2021 to February 2022) and successfully identified lineages of wild-type, alpha, delta, omicron BA.1 and BA.2 as well as their compositions in the samples. The transition of these variants was in good agreement with the epidemic situation reported in Kyoto city during that period based on clinical testing. These data indicate that our NGS-based method is useful for detecting and tracking emerging variants of SARS-CoV-2 in sewage samples. Coupled with the advantages of WBE, this method has the potential to serve as an efficient and low cost means for the community risk assessment of SARS-CoV-2 infection.

Occurrences of similar viral diversity in campus wastewater and reclaimed water of a university dormitory.

Water reuse from wastewater sources still remain some critical safety concerns associated with treacherous contaminants like pathogenic viruses. In this study, viral diversities in campus wastewater (CWW) and its reclaimed water (RCW) recycled for toilet flushing and garden irrigation of a university dormitory were assessed using metagenomic sequencing for acquisition of more background data. Results suggested majority (>80%) of gene sequences within assembled contigs predicted by open reading frame (ORF) finder were no-hit yet believed to be novel/unrevealed viral genomic information whereas hits matched bacteriophages (i.e., mainly Myoviridae, Podoviridae, and Siphoviridae families) were predominant in both CWW and RCW samples. Moreover, few pathogenic viruses (<1%) related to infections of human skin (e.g., Molluscum contagiosum virus, MCV), digestion system (e.g., hepatitis C virus, HCV), and gastrointestinal tract (e.g., human norovirus, HuNoV) were also noticed raising safety concerns about application of reclaimed waters. Low-affinity interactions of particular viral exterior proteins (e.g., envelope glycoproteins or spike proteins) for disinfectant ligand (e.g., chlorite) elucidated treatment limitations of current sewage processing systems even with membrane bioreactor and disinfectant contactor. Revolutionary disinfection approaches together with routine monitoring and new regulations are prerequisite to secure pathogen-correlated water quality for safer reuse of reclaimed waters.

SARS-CoV-2 detection and inactivation in water and wastewater: review on analytical methods, limitations and future research recommendations.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been detected in wastewater. Wastewater-based epidemiology (WBE) is a practical and cost-effective tool for the assessment and controlling of pandemics and probably for examining SARS-CoV-2 presence. Implementation of WBE during the outbreaks is not without limitations. Temperature, suspended solids, pH, and disinfectants affect the stability of viruses in wastewater. Due to these limitations, instruments and techniques have been utilized to detect SARS-CoV-2. SARS-CoV-2 has been detected in sewage using various concentration methods and computer-aided analyzes. RT-qPCR, ddRT-PCR, multiplex PCR, RT-LAMP, and electrochemical immunosensors have been employed to detect low levels of viral contamination. Inactivation of SARS-CoV-2 is a crucial preventive measure against coronavirus disease 2019 (COVID-19). To better assess the role of wastewater as a transmission route, detection, and quantification methods need to be refined. In this paper, the latest improvements in quantification, detection, and inactivation of SARS-CoV-2 in wastewater are explained. Finally, limitations and future research recommendations are thoroughly described.

Wastewater monitoring for detection of public health markers during the COVID-19 pandemic: Near-source monitoring of schools in England over an academic year.

BACKGROUND: Schools are high-risk settings for infectious disease transmission. Wastewater monitoring for infectious diseases has been used to identify and mitigate outbreaks in many near-source settings during the COVID-19 pandemic, including universities and hospitals but less is known about the technology when applied for school health protection. This study aimed to implement a wastewater surveillance system to detect SARS-CoV-2 and other public health markers from wastewater in schools in England. METHODS: A total of 855 wastewater samples were collected from 16 schools (10 primary, 5 secondary and 1 post-16 and further education) over 10 months of school term time. Wastewater was analysed for SARS-CoV-2 genomic copies of N1 and E genes by RT-qPCR. A subset of wastewater samples was sent for genomic sequencing, enabling determination of the presence of SARS-CoV-2 and emergence of variant(s) contributing to COVID-19 infections within schools. In total, >280 microbial pathogens and >1200 AMR genes were screened using RT-qPCR and metagenomics to consider the utility of these additional targets to further inform on health threats within the schools. RESULTS: We report on wastewater-based surveillance for COVID-19 within English primary, secondary and further education schools over a full academic year (October 2020 to July 2021). The highest positivity rate (80.4%) was observed in the week commencing 30th November 2020 during the emergence of the Alpha variant, indicating most schools contained people who were shedding the virus. There was high SARS-CoV-2 amplicon concentration (up to 9.2x106 GC/L) detected over the summer term (8th June - 6th July 2021) during Delta variant prevalence. The summer increase of SARS-CoV-2 in school wastewater was reflected in age-specific clinical COVID-19 cases. Alpha variant and Delta variant were identified in the wastewater by sequencing of samples collected from December to March and June to July, respectively. Lead/lag analysis between SARS-CoV-2 concentrations in school and WWTP data sets show a maximum correlation between the two-time series when school data are lagged by two weeks. Furthermore, wastewater sample enrichment coupled with metagenomic sequencing and rapid informatics enabled the detection of other clinically relevant viral and bacterial pathogens and AMR. CONCLUSIONS: Passive wastewater monitoring surveillance in schools can identify cases of COVID-19. Samples can be sequenced to monitor for emerging and current variants of concern at the resolution of school catchments. Wastewater based monitoring for SARS-CoV-2 is a useful tool for SARS-CoV-2 passive surveillance and could be applied for case identification and containment, and mitigation in schools and other congregate settings with high risks of transmission. Wastewater monitoring enables public health authorities to develop targeted prevention and education programmes for hygiene measures within undertested communities across a broad range of use cases.

Wastewater-based epidemiology for surveillance of infectious diseases in healthcare settings.

PURPOSE OF REVIEW: Wastewater-based surveillance (WBS) (epidemiology) using near-source sampling (NSS) in large buildings, hospitals and care homes is reviewed covering three main areas: state-of-the-art WBS, benefits/opportunities NSS has for hospital infection control systems and new insights from hospital wastewater surveillance and policy implications. RECENT FINDINGS: Wastewater provides aggregate, anonymous sources of data where the spatial resolution can be linked to populations being served. In hospitals, clear links established between wastewater RNA-fragments signal to nosocomial COVID-19 cases/outbreaks. Detecting other targets from hospital wastewater such as antimicrobial resistance markers is considered a substantial opportunity for this technology. Other clinically relevant infections, that is influenza and monkeypox, can be perceived, and sub-variant resolution to target public health response in near real time to benefit hospital infection control. WBS can reduce hospitals' clinical testing requirements, as diagnostic costs are aggregated into fewer samples while still detecting single cases. SUMMARY: WBS using NSS can inform infectious disease monitoring earlier, faster and cheaper than conventional monitoring. Routine sampling using wastewater provides a platform for risk-based sampling and enables smarter allocation of resources. Finally, hospital wastewater can be used for the benefit of the wastewater surveillance field as a promising source to monitor emerging threats and resolve longstanding questions on faecal shedding. Hospital monitoring in low-income settings is considered a priority for future research.

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.

Assessing the effects of COVID-19 restrictions on alcohol consumption in Melbourne, Australia using high-resolution wastewater sampling.

The impact of the COVID-19 pandemic and related restrictions on alcohol consumption in Australia remains unclear. High-resolution daily samples from a wastewater treatment plant (WWTP) which served one of the largest cities in Australia, Melbourne, were analysed for temporal trends in alcohol consumption under extended periods of COVID-19 restrictions in 2020. Melbourne experienced two major lockdowns in 2020, which divided the year of 2020 into five periods (pre-lockdown, first lockdown, between lockdown, second lockdown and post second-lockdown). In this study, daily sampling identified shifts in alcohol consumption during different periods of restrictions. Alcohol consumption in the first lockdown period, when bars closed and social and sports events ceased, was lower than pre-lockdown period. However, alcohol consumption was higher in the second lockdown period than the previous lockdown period. There were spikes in alcohol consumption at the start and end of each lockdown (except for post lockdown). For most of 2020, the usual weekday-weekend variations in alcohol consumption were less evident but there was a significant difference in alcohol consumption between weekdays and weekends after the second lockdown. This suggests that drinking patterns eventually returned to normal after the end of the second lockdown. This study demonstrates the usefulness of high-resolution wastewater sampling in evaluating the effects on alcohol consumption of social interventions in specific temporal locations.

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

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

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.

Monitoring influenza and respiratory syncytial virus in wastewater. Beyond COVID-19.

Wastewater-based surveillance can be a valuable tool to monitor viral circulation and serve as an early warning system. For respiratory viruses that share similar clinical symptoms, namely SARS-CoV-2, influenza, and respiratory syncytial virus (RSV), identification in wastewater may allow differentiation between seasonal outbreaks and COVID-19 peaks. In this study, to monitor these viruses as well as standard indicators of fecal contamination, a weekly sampling campaign was carried out for 15 months (from September 2021 to November 2022) in two wastewater treatment plants that serve the entire population of Barcelona (Spain). Samples were concentrated by the aluminum hydroxide adsorption-precipitation method and then analyzed by RNA extraction and RT-qPCR. All samples were positive for SARS-CoV-2, while the positivity rates for influenza virus and RSV were significantly lower (10.65 % for influenza A (IAV), 0.82 % for influenza B (IBV), 37.70 % for RSV-A and 34.43 % for RSV-B). Gene copy concentrations of SARS-CoV-2 were often approximately 1 to 2 logarithmic units higher compared to the other respiratory viruses. Clear peaks of IAV H3:N2 in February and March 2022 and RSV in winter 2021 were observed, which matched the chronological incidence of infections recorded in the Catalan Government clinical database. In conclusion, the data obtained from wastewater surveillance provided new information on the abundance of respiratory viruses in the Barcelona area and correlated favorably with clinical data.

Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants.

(MOTIVATION): Wastewater-based epidemiology (WBE) has emerged as a promising approach for monitoring the COVID-19 pandemic, since the measurement process is cost-effective and is exposed to fewer potential errors compared to other indicators like hospitalization data or the number of detected cases. Consequently, WBE was gradually becoming a key tool for epidemic surveillance and often the most reliable data source, as the intensity of clinical testing for COVID-19 drastically decreased by the third year of the pandemic. Recent results suggests that the model-based fusion of wastewater measurements with clinical data and other indicators is essential in future epidemic surveillance. (METHOD): In this work, we developed a wastewater-based compartmental epidemic model with a two-phase vaccination dynamics and immune evasion. We proposed a multi-step optimization-based data assimilation method for epidemic state reconstruction, parameter estimation, and prediction. The computations make use of the measured viral load in wastewater, the available clinical data (hospital occupancy, delivered vaccine doses, and deaths), the stringency index of the official social distancing rules, and other measures. The current state assessment and the estimation of the current transmission rate and immunity loss allow a plausible prediction of the future progression of the pandemic. (RESULTS): Qualitative and quantitative evaluations revealed that the contribution of wastewater data in our computational epidemiological framework makes predictions more reliable. Predictions suggest that at least half of the Hungarian population has lost immunity during the epidemic outbreak caused by the BA.1 and BA.2 subvariants of Omicron in the first half of 2022. We obtained a similar result for the outbreaks caused by the subvariant BA.5 in the second half of 2022. (APPLICABILITY): The proposed approach has been used to support COVID management in Hungary and could be customized for other countries as well.

Respiratory virus concentrations in human excretions that contribute to wastewater: a systematic review and meta-analysis.

Concentrations of nucleic acids from a range of respiratory viruses in wastewater solids collected from wastewater treatment plants correlate to clinical data on disease occurrence in the community contributing to the wastewater. Viral nucleic acids enter wastewater from excretions deposited in toilets or drains. To relate measured concentrations in wastewater at a treatment plant to the number of community infections, viral nucleic-acid concentrations in human excretions are needed as inputs to a mass balance model. Here, we carried out a systematic review and meta-analysis to characterize the concentrations and presence of influenza A and B, respiratory syncytial virus, metapneumovirus, parainfluenza virus, rhinovirus, and seasonal coronaviruses in stool, urine, mucus, sputum, and saliva. We identified 220 data sets from 50 articles and reported viral concentrations and presence in these excretions. Data were unevenly distributed across virus type (with the most available for influenza) and excretion type (with the most available for respiratory excretions). Most articles only reported the presence or absence of the virus in a cross-sectional study design. There is a need for more concentration data, including longitudinal data, across all respiratory virus and excretion types. Such data would allow quantitatively linking virus wastewater concentrations to numbers of infected individuals.

Environmental genomic surveillance of SARS-CoV-2 in wastewater in Rio de Janeiro, Brazil.

Wastewater-based epidemiology can be a complementary approach for monitoring SARS-CoV-2 prevalence, diversity, and geographic distribution. It is a complementary approach regarding its prevalence and diversity, and geographic distribution. The study aimed to evaluate the genetic diversity of SARS-CoV-2 in two wastewater treatment plants (WWTPs) in Rio de Janeiro, Brazil. Samples were collected over a period of January to December 2021 and were concentrated with PEG8000 and the presence of SARS-CoV-2 was detected using E and N1 genes. Partial sequencing of the SARS-CoV-2 genomes resulted in the identification of variants of concern and variants of interest throughout the collection period. It was possible to identify the Mu, Delta, Gamma and Omicron variants in WWTP1; on the contrary, no variants were observed in WWTP2. To the best of our knowledge, we detected the variant Mu (B.1.621) containing characteristic mutations (S:E484K, S:N501Y) from WWTP, for the first time, in Brazil. Another Mu variant detected from clinical surveillance was announced one month after our finding. The detection of SARS-CoV-2 in wastewater can serve as a tool to monitor the prevalence and epidemiology in each community, helping to understand the spread of the virus among the population.

Wastewater-based prediction of COVID-19 cases using a random forest algorithm with strain prevalence data: A case study of five municipalities in Latvia.

Wastewater-based epidemiology (WBE) is a rapid and cost-effective method that can detect SARS-CoV-2 genomic components in wastewater and can provide an early warning for possible COVID-19 outbreaks up to one or two weeks in advance. However, the quantitative relationship between the intensity of the epidemic and the possible progression of the pandemic is still unclear, necessitating further research. This study investigates the use of WBE to rapidly monitor the SARS-CoV-2 virus from five municipal wastewater treatment plants in Latvia and forecast cumulative COVID-19 cases two weeks in advance. For this purpose, a real-time quantitative PCR approach was used to monitor the SARS-CoV-2 nucleocapsid 1 (N1), nucleocapsid 2 (N2), and E genes in municipal wastewater. The RNA signals in the wastewater were compared to the reported COVID-19 cases, and the strain prevalence data of the SARS-CoV-2 virus were identified by targeted sequencing of receptor binding domain (RBD) and furin cleavage site (FCS) regions employing next-generation sequencing technology. The model methodology for a linear model and a random forest was designed and carried out to ascertain the correlation between the cumulative cases, strain prevalence data, and RNA concentration in the wastewater to predict the COVID-19 outbreak and its scale. Additionally, the factors that impact the model prediction accuracy for COVID-19 were investigated and compared between linear and random forest models. The results of cross-validated model metrics showed that the random forest model is more effective in predicting the cumulative COVID-19 cases two weeks in advance when strain prevalence data are included. The results from this research help inform WBE and public health recommendations by providing valuable insights into the impact of environmental exposures on health outcomes.

Enabling accurate and early detection of recently emerged SARS-CoV-2 variants of concern in wastewater.

As clinical testing declines, wastewater monitoring can provide crucial surveillance on the emergence of SARS-CoV-2 variant of concerns (VoCs) in communities. In this paper we present QuaID, a novel bioinformatics tool for VoC detection based on quasi-unique mutations. The benefits of QuaID are three-fold: (i) provides up to 3-week earlier VoC detection, (ii) accurate VoC detection (>95% precision on simulated benchmarks), and (iii) leverages all mutational signatures (including insertions & deletions).

Online dashboards for SARS-CoV-2 wastewater data need standard best practices: An environmental health communication agenda.

The COVID-19 pandemic has highlighted the benefits of wastewater surveillance to supplement clinical data. Numerous online information dashboards have been rapidly, and typically independently, developed to communicate environmental surveillance data to public health officials and the public. In this study, we review dashboards presenting SARS-CoV-2 wastewater data and propose a path toward harmonization and improved risk communication. A list of 127 dashboards representing 27 countries was compiled. The variability was high and encompassed aspects including the graphics used for data presentation (e.g., line/bar graphs, maps, and tables), log versus linear scale, and 96 separate ways of labeling SARS-CoV-2 wastewater concentrations. Globally, dashboard presentations also differed by region. Approximately half of the dashboards presented clinical case data, and 25% presented variant monitoring. Only 30% of dashboards provided downloadable source data. While any single dashboard is likely useful in its own context and locality, the high variation across dashboards at best prevents optimal use of wastewater surveillance data on a broader geographical scale and at worst could lead to risk communication issues and the potential for public health miscommunication. There is a great opportunity to improve scientific communication through the adoption of uniform data presentation conventions, standards, and best practices in this field.

Monkeypox viral nucleic acids detected using both DNA and RNA extraction workflows.

Molecular methods have been used to detect human pathogens in wastewater with sampling typically performed at wastewater treatment plants (WWTP) and upstream locations within the sewer system. A wastewater-based surveillance (WBS) program was established at the University of Miami (UM) in 2020, which included measurements of SARS-CoV-2 levels in wastewater from its hospital and within the regional WWTP. In addition to the development of a SARS-CoV-2 quantitative PCR (qPCR) assay, qPCR assays to detect other human pathogens of interest were also developed at UM. Here we report on the use of a modified set of reagents published by the CDC to detect nucleic acids of Monkeypox virus (MPXV) which emerged during May of 2022 to become a concern worldwide. Samples collected from the University hospital and from the regional WWTP were processed through DNA and RNA workflows and analyzed by qPCR to detect a segment of the MPXV CrmB gene. Results show positive detections of MPXV nucleic acids in the hospital and wastewater treatment plant wastewater which coincided with clinical cases in the community and mirrored the overall trend of nationwide MPXV cases reported to the CDC. We recommend the expansion of current WBS programs' methods to detect a broader range of pathogens of concern in wastewater and present evidence that viral RNA in human cells infected by a DNA virus can be detected in wastewater.

Disinfection byproducts of iopamidol, iohexol, diatrizoate and their distinct acute toxicity on Scenedesmus sp., Daphnia magna and Danio rerio.

The COVID-19 pandemic resulted in increasing the usage of iodinated contrast media (ICM), and thus an increase in the prevalence of ICM-contaminated wastewater. While ICM is generally safe, this has the potential to be problematic because as medical wastewater is treated and disinfected, various ICM-derived disinfection byproducts (DBPs) may be generated and released into the environment. However, little information was available about whether ICM-derived DBPs are toxic to aquatic organisms. In this study, the degradation of three typical ICM (iopamidol, iohexol, diatrizoate) at initial concentration of 10 µM and 100 µM in chlorination and peracetic acid without or with NH4+ was investigated, and the potential acute toxicity of treated disinfected water containing potential ICM-derived DBPs on Daphnia magna, Scenedesmus sp. and Danio rerio was tested. The degradation results suggested that only iopamidol was significantly degraded (level of degradation >98%) by chlorination, and the degradation rate of iohexol and diatrizoate were significantly increased in chlorination with NH4+. All three ICM were not degraded in peracetic acid. The toxicity analysis results indicate that only the disinfected water of iopamidol and iohexol by chlorination with NH4+ were toxic to at least one aquatic organism. These results highlighted that the potential ecological risk of ICM-contained medical wastewater by chlorination with NH4+ should not be neglected, and peracetic acid may be an environment-friendly alternative for the disinfection of wastewater containing ICM.

Antiviral drugs in wastewater are on the rise as emerging contaminants: A comprehensive review of spatiotemporal characteristics, removal technologies and environmental risks.

Antiviral drugs (ATVs) are widely used to treat illnesses caused by viruses. Particularly, ATVs were consumed in such large quantities during the pandemic that high concentrations were detected in wastewater and aquatic environment. Since ATVs are not fully absorbed by the human or animal body, this results in large amounts of them being discharged into the sewage through urine or feces. Most ATVs can be degraded by microbes at wastewater treatment plants (WWTPs), while some ATVs either require deep treatment to reduce concentration and toxicity. Parent and metabolites residing in effluent posed a varying degree of risk when entering the aquatic environment, while increasing the potential of natural reservoirs for environmentally acquired antiviral drug resistance potential. There is a rising research on the behavior of ATVs in the environment has surged since the pandemic. In the context of multiple viral diseases worldwide, especially during the current COVID-19 pandemic, a comprehensive assessment of the occurrence, removal, and risk of ATVs is urgently needed. This review aims to discuss the fate of ATVs in WWTPs from various regions in the world with wastewater as the main analyzing object. The ultimate goal is to focus on ATVs with high ecological impact and regulate their use or develop advanced treatment technologies to mitigate the risk to the environment.