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

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

Removal performance of SARS-CoV-2 in wastewater treatment by membrane bioreactor, anaerobic-anoxic-oxic, and conventional activated sludge processes.

The potential risk of SARS-CoV-2 in treated effluent from a wastewater treatment plant (WWTP) is concerned since SARS-CoV-2 is contained in wastewater during the COVID-19 outbreak. However, the removal of SARS-CoV-2 in WWTP has not been well investigated. The objectives of this study were (i) to clarify the removal performance of SARS-CoV-2 during wastewater treatment, (ii) to compare the removal performance of different secondary treatment processes, and (iii) to evaluate applicability of pepper mild mottle of virus (PMMoV) as a performance indicator for the reduction of SARS-CoV-2 RNA in wastewater treatment. Influent wastewater, secondary-treatment effluent (before chlorination), and final effluent (after chlorination) samples were collected from a WWTP from May 28 to September 24, 2020, during the COVID-19 outbreak in Japan. The target WWTP had three parallel treatment systems employing conventional activated sludge (CAS), anaerobic-anoxic -oxic (A2O), and membrane bioreactor (MBR) processes. SARS-CoV-2 in both the liquid and solid fractions of the influent wastewater was concentrated and quantified using RT-qPCR. SARS-CoV-2 in treated effluent was concentrated from 10 L samples to achieve a detection limit as low as 10 copies/L. The log reduction value (LRV) of SARS-CoV-2 was 2.7 ± 0.86 log10 in CAS, 1.6 ± 0.50 log10 in A2O, and 3.6 ± 0.62 log10 in MBR. The lowest LRV observed during the sampling period was 2.8 log10 in MBR, 1.2 log10 in CAS, and 1.0 log10 in A2O process, indicating that the MBR had the most stable reduction performance. PMMoV was found to be a good indicator virus to evaluate reduction performance of SARS-CoV-2 independent of the process configuration because the LRV of PMMoV was significantly lower than that of SARS-CoV-2 in the CAS, A2O and MBR processes.

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.

SARS-CoV-2 shedding sources in wastewater and implications for wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) approach for COVID-19 surveillance is largely based on the assumption of SARS-CoV-2 RNA shedding into sewers by infected individuals. Recent studies found that SARS-CoV-2 RNA concentration in wastewater (CRNA) could not be accounted by the fecal shedding alone. This study aimed to determine potential major shedding sources based on literature data of CRNA, along with the COVID-19 prevalence in the catchment area through a systematic literature review. Theoretical CRNA under a certain prevalence was estimated using Monte Carlo simulations, with eight scenarios accommodating feces alone, and both feces and sputum as shedding sources. With feces alone, none of the WBE data was in the confidence interval of theoretical CRNA estimated with the mean feces shedding magnitude and probability, and 63% of CRNA in WBE reports were higher than the maximum theoretical concentration. With both sputum and feces, 91% of the WBE data were below the simulated maximum CRNA in wastewater. The inclusion of sputum as a major shedding source led to more comparable theoretical CRNA to the literature WBE data. Sputum discharging behavior of patients also resulted in great fluctuations of CRNA under a certain prevalence. Thus, sputum is a potential critical shedding source for COVID-19 WBE surveillance.

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.

Sewage surveillance for SARS-CoV-2: Molecular detection, quantification, and normalization factors.

The presence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in wastewater systems provides a primary indication of the coronavirus disease 2019 (COVID-19) spread throughout communities worldwide. Droplet digital polymerase chain reaction (dd-PCR) or reverse transcription-polymerase chain reaction (RT-PCR) administration of SARS-CoV-2 in wastewaters provides a reliable and efficient technology for gathering secondary local-level public health data. Often the accuracy of prevalence estimation is hampered by many methodological issues connected with wastewater surveillance. Still, more studies are needed to use and create efficient approaches for deciphering the actual SARS-CoV-2 indication from noise in the specimens/samples. Nearly 39-65% of positive patients and asymptomatic carriers expel the virus through their faeces however, only ∼6% of the infected hosts eject it through their urine. COVID-19 positive patients can shed the remnants of the SARS-CoV-2 RNA virus within the concentrations ∼103-108 copies/L. However, it can decrease up to 102 copies/L in wastewaters due to dilution. Environmental virology and microbiology laboratories play a significant role in the identification and analysis of SARS-CoV-2 ribonucleic acid (RNA) in waste and ambient waters worldwide. Virus extraction or recovery from the wastewater (However, due to lack of knowledge, established procedures, and integrated quality assurance/quality control (QA/QC) approaches, the novel coronavirus RNA investigation for estimating current illnesses and predicting future outbreaks is insufficient and/or conducted inadequately. The present manuscript is a technical review of the various methods and factors considered during the identification of SARS-CoV-2 genetic material in wastewaters and/or sludge, including tips and tricks to be taken care of during sampling, virus concentration, normalization, PCR inhibition, and trend line smoothening when compared with clinically active/positive cases.

Selection of surrogate viruses for process control in detection of SARS-CoV-2 in wastewater.

Since SARS-CoV-2 RNA in wastewater is often present at low concentration or under detection limit, ensuring the reliability of detection processes using appropriate process controls is essential. The objective of this study was to evaluate applicability and limitations of candidate surrogate viruses as process controls under combinations of different virus concentration and RNA extraction methods. Detection efficiency of SARS-CoV-2 spiked in wastewater was compared with those of candidate surrogate viruses of bacteriophage ϕ6, pepper mild mottle virus (PMMoV), F-specific coliphage (F-phage), and murine norovirus (MNV). After inactivated SARS-CoV-2 and ϕ6 were spiked in two different wastewaters, the viruses in solid and liquid fractions of wastewater were concentrated by centrifuge and polyethylene glycol (PEG) precipitation, respectively. Viral RNA was extracted by using QIAamp Viral RNA Mini Kit and 3 other commercially available extraction kits, then quantified by reverse transcription-quantitative PCR using CDCN1 assay. Regardless of extraction kits, SARS-CoV-2 was consistently detected with good efficiency from both liquid (11-200%) and solid fractions (7.1-93%). Among the candidate process controls, PMMoV was widely detected at good efficiencies from both liquid and solid fractions regardless of selection of RNA extraction kits. F-phage and MNV also showed good detection efficiencies in most combinations of wastewater fractions and RNA extraction kits. An enveloped virus ɸ6 was found often undetected or to have very low detection efficiency (0.1-4.2%) even when SARS-CoV-2 spiked in wastewater was detected with good efficiency. Consequently, PMMoV is widely applicable as process control for detection of SARS-CoV-2 either in liquid fractions concentrated by PEG precipitation, or in solid fractions concentrated by centrifuge.

Electrochemical and Mechanistic Study of Oxidative Degradation of Favipiravir by Electrogenerated Superoxide through Proton-Coupled Electron Transfer.

Electrochemical analyses aided by density functional theory calculations were used to investigate the oxidative degradation of pyrazine antiviral drugs, 3-hydroxypyrazine-2-carboxamide (T-1105) and 6-fluoro-3-hydroxypyrazine-2-carboxamide (favipiravir, T-705), by the electrogenerated superoxide radical anion (O2 •-). T-1105 and T-705 are antiviral RNA nucleobase analogues that selectively inhibit the RNA-dependent RNA polymerase. They are expected as a drug candidate against various viral infections, including COVID-19. The pyrazine moiety was decomposed by O2 •- through proton-coupled electron transfer (PCET). Our results show that its active form, pyrazine-ribofuranosyl-5'-triphosphate, is easily oxidized under inflamed organs by overproduced O2 •- through the PCET mechanism in the immune system. This mechanistic study implies that the oxidative degradation of pyrazine derivatives will be prevented by controlling the PCET through simple modification of the pyrazine structure.

Making Waves Perspectives of Modelling and Monitoring of SARS-CoV-2 in Aquatic Environment for COVID-19 Pandemic.

Prevalence of SARS-CoV-2 in the aquatic environment pertaining to the COVID-19 pandemic has been a global concern. Though SARS-CoV-2 is known as a respiratory virus, its detection in faecal matter and wastewater demonstrates its enteric involvement resulting in vulnerable aquatic environment. Here, we provide the latest updates on wastewater-based epidemiology, which is gaining interest in the current situation as a unique tool of surveillance and monitoring of the disease. Transport pathways with its migration through wastewater to surface and subsurface waters, probability of infectivity and ways of inactivation of SARS-CoV-2 are discussed in detail. Epidemiological models, especially compartmental projections, have been explained with an emphasis on its limitation and the assumptions on which the future predictions of disease propagation are based. Besides, this review covers various predictive models to track and project disease spread in the future and gives an insight into the probability of a future outbreak of the disease.

Potential discharge, attenuation and exposure risk of SARS-CoV-2 in natural water bodies receiving treated wastewater

Recently reported detection of SARS-CoV-2 in wastewater around the world has led to emerging concerns on potential risk in water bodies receiving treated wastewater effluent. This review aims to provide an up-to-date state of key knowledge on the impact of SARS-CoV-2 in natural water bodies receiving treated wastewater. In this review, SARS-CoV-2 concentrations in wastewater, expected removal in WWTPs, and possible dilution and decay in water bodies are reviewed based on past studies on SARS-CoV-2 and related enveloped viruses. We suggest a quantitative microbial risk assessment (QMRA) framework to estimate the potential risk of SARS-CoV-2 in natural water bodies through various water activities. Dose–response model of SARS-CoV and Poisson’s distribution is employed to estimate possible viral ingestion and the annual chance of infection through several water activities in natural water bodies. Finally, future perspectives and research needs have been addressed to overcome the limitations and uncertainty in the risk assessment of SARS-CoV-2 in natural water bodies.

Detection of SARS-CoV-2 in wastewater in Japan during a COVID-19 outbreak.

The presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater samples has been documented in several countries. Wastewater-based epidemiology (WBE) is potentially effective for early warning of a COVID-19 outbreak. In this study, presence of SARS-CoV-2 RNA in wastewater samples was investigated and was compared with the number of the confirmed COVID-19 cases in the study area during COVID-19 outbreak in Japan. In total, 45 influent wastewater samples were collected from five wastewater treatment plants in Ishikawa and Toyama prefectures in Japan. During the study period, the numbers of confirmed COVID-19 cases in these prefectures increased from 0.3 and 0 to >20 per 100,000 people. SARS-CoV-2 ribonucleic acid (RNA) in the samples was detected using several PCR-based assays. Of the 45 samples, 21 were positive for SARS-CoV-2 according to at least one of the three quantitative RT-PCR assays. The detection frequency increased when the number of total confirmed SARS-CoV-2 cases in 100,000 people exceeded 10 in each prefecture; however, SARS-CoV-2 could also be detected at a low frequency even when the number was below 1.0. SARS-CoV-2 in wastewater could be detected in the early stage of the epidemic, even if the number of confirmed cases potentially underestimates the actual numbers of cases. This suggests that WBE approach can potentially act as an early warning of COVID-19 outbreaks in Japan.