The ongoing global pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a Public Health Emergency of International Concern, which was officially declared by the World Health Organization. SARS-CoV-2 is a member of the family Coronaviridae that consists of a group of enveloped viruses with single-stranded RNA genome, which cause diseases ranging from common colds to acute respiratory distress syndrome. Although the major transmission routes of SARS-CoV-2 are inhalation of aerosol/droplet and person-to-person contact, currently available evidence indicates that the viral RNA is present in wastewater, suggesting the need to better understand wastewater as potential sources of epidemiological data and human health risks. Here, we review the current knowledge related to the potential of wastewater surveillance to understand the epidemiology of COVID-19, methodologies for the detection and quantification of SARS-CoV-2 in wastewater, and information relevant for human health risk assessment of SARS-CoV-2. There has been growing evidence of gastrointestinal symptoms caused by SARS-CoV-2 infections and the presence of viral RNA not only in feces of infected individuals but also in wastewater. One of the major challenges in SARS-CoV-2 detection/quantification in wastewater samples is the lack of an optimized and standardized protocol. Currently available data are also limited for conducting a quantitative microbial risk assessment (QMRA) for SARS-CoV-2 exposure pathways. However, modeling-based approaches have a potential role to play in reducing the impact of the ongoing COVID-19 outbreak. Furthermore, QMRA parameters obtained from previous studies on relevant respiratory viruses help to inform risk assessments of SARS-CoV-2. Our understanding on the potential role of wastewater in SARS-CoV-2 transmission is largely limited by knowledge gaps in its occurrence, persistence, and removal in wastewater. There is an urgent need for further research to establish methodologies for wastewater surveillance and understand the implications of the presence of SARS-CoV-2 in wastewater.
Wastewater-based epidemiology is a powerful tool to understand the actual incidence of coronavirus disease 2019 (COVID-19) in a community because severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of COVID-19, can be shed in the feces of infected individuals regardless of their symptoms. The present study aimed to assess the presence of SARS-CoV-2 RNA in wastewater and river water in Yamanashi Prefecture, Japan, using four quantitative and two nested PCR assays. Influent and secondary-treated (before chlorination) wastewater samples and river water samples were collected five times from a wastewater treatment plant and three times from a river, respectively, between March 17 and May 7, 2020. The wastewater and river water samples (200–5000 mL) were processed by using two different methods: the electronegative membrane-vortex (EMV) method and the membrane adsorption-direct RNA extraction method. Based on the observed concentrations of indigenous pepper mild mottle virus RNA, the EMV method was found superior to the membrane adsorption-direct RNA extraction method. SARS-CoV-2 RNA was successfully detected in one of five secondary-treated wastewater samples with a concentration of 2.4 × 103 copies/L by N_Sarbeco qPCR assay following the EMV method, with sequence confirmation of the qPCR product, whereas all the influent samples were tested negative for SARS-CoV-2 RNA. This result could be attributed to higher limit of detection for influent (4.0 × 103–8.2 × 104 copies/L) with a lower filtration volume (200 mL) compared to that for secondary-treated wastewater (1.4 × 102–2.5 × 103 copies/L) with a higher filtration volume of 5000 mL. None of the river water samples tested positive for SARS-CoV-2 RNA. Comparison with the reported COVID-19 cases in Yamanashi Prefecture showed that SARS-CoV-2 RNA was detected in the secondary-treated wastewater sample when the cases peaked in the community. This is the first study reporting the detection of SARS-CoV-2 RNA in wastewater in Japan.
There is currently a clear benefit for many countries to utilize wastewater-based epidemiology (WBE) as part of ongoing measures to manage the coronavirus disease 2019 (COVID-19) global pandemic. Since most wastewater virus concentration methods were developed and validated for nonenveloped viruses, it is imperative to determine the efficiency of the most commonly used methods for the enveloped severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Municipal wastewater seeded with a human coronavirus (CoV) surrogate, murine hepatitis virus (MHV), was used to test the efficiency of seven wastewater virus concentration methods: (A–C) adsorption-extraction with three different pre-treatment options, (D–E) centrifugal filter device methods with two different devices, (F) polyethylene glycol (PEG 8000) precipitation, and (G) ultracentrifugation. MHV was quantified by reverse-transcription quantitative polymerase chain reaction and the recovery efficiency was calculated for each method. The mean MHV recoveries ranged from 26.7 to 65.7%. The most efficient methods were adsorption-extraction methods with MgCl2 pre-treatment (Method C), and without pre-treatment (Method B). The third most efficient method used the Amicon® Ultra-15 centrifugal filter device (Method D) and its recovery efficiency was not statistically different from the most efficient methods. The methods with the worst recovery efficiency included the adsorption-extraction method with acidification (A), followed by PEG precipitation (F). Our results suggest that absorption-extraction methods with minimal or without pre-treatment can provide suitably rapid, cost-effective and relatively straightforward recovery of enveloped viruses in wastewater. The MHV is a promising process control for SARS-CoV-2 surveillance and can be used as a quality control measure to support community-level epidemic mitigation and risk assessment.
1 November 2020 in Science of The Total Environment