key: cord-1054245-4om2u914 authors: Ahmed, Warish; Angel, Nicola; Edson, Janette; Bibby, Kyle; Bivins, Aaron; O'Brien, Jake W.; Choi, Phil M.; Kitajima, Masaaki; Simpson, Stuart L.; Li, Jiaying; Tscharke, Ben; Verhagen, Rory; Smith, Wendy J.M.; Zaugg, Julian; Dierens, Leanne; Hugenholtz, Philip; Thomas, Kevin V.; Mueller, Jochen F. title: First confirmed detection of SARS-CoV-2 in untreated wastewater in Australia: A proof of concept for the wastewater surveillance of COVID-19 in the community date: 2020-04-18 journal: Sci Total Environ DOI: 10.1016/j.scitotenv.2020.138764 sha: 9f3753a54a52855c5a4d801cfd8f4e5ce712a2ab doc_id: 1054245 cord_uid: 4om2u914 Abstract Infection with SARS-CoV-2, the etiologic agent of the ongoing COVID-19 pandemic, is accompanied by the shedding of the virus in stool. Therefore, the quantification of SARS-CoV-2 in wastewater affords the ability to monitor the prevalence of infections among the population via wastewater-based epidemiology (WBE). In the current work, SARS-CoV-2 RNA was concentrated from wastewater in a catchment in Australia and viral RNA copies were enumerated using reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) resulting in two positive detections within a six day period from the same wastewater treatment plant (WWTP). The estimated RNA copy numbers observed in the wastewater were then used to estimate the number of infected individuals in the catchment via Monte Carlo simulation. Given the uncertainty and variation in the input parameters, the model estimated a median range of 171 to 1090 infected persons in the catchment, which is in reasonable agreement with clinical observations. This work highlights the viability of WBE for monitoring infectious diseases, such as COVID-19, in communities. The work also draws attention to the need for further methodological and molecular assay validation for enveloped viruses in wastewater. J o u r n a l P r e -p r o o f The ongoing global pandemic of coronavirus disease 2019 , caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been a public health emergency of international concern (WHO, 2020). The reported symptoms of COVID-19 patients include cough, fever, difficulty in breathing and diarrhea, and SARS-CoV-2 ribonucleic acid (RNA) has been detected in faeces of not only symptomatic but also asymptomatic patients (Gao et al., 2020; Holshue et al., 2020; Jiehao et al., 2020; Tang et al., 2020; Wölfel et al., 2020; Zhang et al., 2020; Zhang et al., 2020) . These clinical observations imply that municipal wastewater of affected communities might contain the virus. Wastewaterbased epidemiology (WBE) is a promising approach to understand the prevalence of viruses in a given wastewater treatment plant (WWTP) catchment population, because wastewater contains viruses excreted from symptomatic and asymptomatic individuals in a catchment (Sinclair et al., 2008; Xagoraraki and O'Brien, 2020) . WBE is especially useful for early warning of disease outbreaks and informing the efficacy of public health interventions, as previously demonstrated for enteric viruses, such as norovirus, hepatitis A virus, and poliovirus (Hellmér et al. 2014; Asghar et al., 2014) . In Australia, the first case of was recorded on January 25, 2020, and there have been >6,300 confirmed cases as of April 13, 2020 (Australian Government Department of Health, 2020). In the State of Queensland, there have been 998 cases of COVID-19 recorded on April 14, 2020. The first case of COVID-19 was reported in Brisbane on Feb 21, 2020 (two passengers from a Diamond Princess Cruise Ship) and increased to 541 confirmed cases on the 14 th April, 2020 in Queensland's Brisbane North and Brisbane South Primary Health Networks (PHN). There has to date been no report on the detection of SARS-CoV-2 in wastewater in Australia, although a few recent studies conducted in other parts of the world (i.e., the Netherlands and USA) have reported molecular detection of SARS-CoV-2 in wastewater samples (Lodder and J o u r n a l P r e -p r o o f Untreated wastewater (sewage) samples were collected from one suburban pumping station (PS) and two WWTPs representing urban catchments in Southeast Queensland (SEQ). The two WWTP catchments represent approximately 21% (WWTP A) and 50% (WWTP B) of the combined populations of the two PHNs (Fig. 1 ). Fig. 2a and b showing sampling dates, the number of cases and the potential detection windows (28 days) of SARS-CoV-2 for wastewater samples in the two PHNs (Wu et al., 2020c) . Sampling personnel wore face standard personal protective equipment (PPE) for wastewater sampling, such as long pants, steel capped boots, hard hats, safety glasses and gloves. Samples were collected using two types of automated sampling techniqueseither a conventional refrigerated autosampler or a submersible in-situ high frequency autosampler (at WWTP A) as well as grab sampling techniques (pumping station and WWTP B). Samples were transported on ice to the laboratory and stored at 4ºC until further analysis. Viruses were concentrated using two previously published methods. These methods are referred to as Method A (direct RNA extraction from electronegative membranes) (Ahmed et al. 2015) and Method B (ultrafiltration) (Ikner et al., 2011) . Method A began with adjustment of the sample pH to ~3.5 to 4 using 2.0 N HCl. Connect platform was used to extract RNA to a final volume of 100 μL. Recently published RT-qPCR assays were used for the detection of SARS-CoV-2 in wastewater samples Shirato et al., 2020) . The sequences for primers and probes are shown in Table 1 An experiment was conducted to determine the presence of RT-qPCR inhibition in RNA extracted from wastewater samples using a Sketa22 real-time PCR assay (Haugland et al., 2005) . A known copy (10 J o u r n a l P r e -p r o o f stored at -80°C and subjected to RT-qPCR analysis within the same day after RNA extraction. A reagent blank and extraction blank were included for each batch of RNA extraction to ensure no carryover contamination occurred during RNA extraction. No carryover contamination was observed in reagent blank samples. To minimize potential RT-qPCR contamination, RNA extraction and RT-qPCR setup were performed in separate laboratories. TaqMan RT-qPCR products (wastewater sample collected on 26/03/2020) were sequenced with CoverM 'filter' (minimum identity 90% and minimum aligned length of 75%). Read depth profiles for each sample were calculated using samtools (ver. 1.9). The prevalence of SARS-CoV-2 infection within the catchment was estimated using a mass balance on the total number of RNA copies in wastewater each day, as measured in wastewater by RT-qPCR, and the number of SARS-CoV-2RNA copies shed in stool by an infected individual each day (Equation 1). None of the wastewater RNA samples had RT-qPCR inhibition, as confirmed by the Sketa22 RT-qPCR assay. ) values for N_Sarbeco and NIID_2019-nCOV_N were 0.995 and 0.998%, respectively. Among the nine wastewater samples tested, two ( J o u r n a l P r e -p r o o f and 1.9 copies/100 mL of untreated wastewater, respectively. The aligned forward and reverse Sanger sequences confirmed a 100% identity match to the SARS-COV-2 isolate and aligned to the N-protein (28200-29500) (Wu et al., 2020b) . This result was further confirmed with the Illumina MiSeq sequencing. Specifically, the quality-controlled reads in the region with the highest coverage were primarily mapped to positions ~28,700 to 28,800 of the SARS-CoV2/ISR_IT0320/human/2020/ISR genome. Since the probability distributions for two input variables are right skewed in arithemetic space, the model summary statistic is reported as the median and 95% confidence interval In this proof of concept study, we investigated whether the presence of SARS-CoV-2 in untreated wastewater can be used as an early warning for COVID-19 infections in communities. For the detection of SARS-CoV-2, the N_Sarbeco and NIID_2019-nCOV_N assays were used based on results published in a recent study that reported the improved performance of these two assays against the synthesized control RNA template in the Journal Pre-proof QuantiTect assay (Shirato et al., 2020) . Subsequently, these two assays were used as diagnostic test systems in Japan. As far as we are aware, 16 RT-PCR assays have been developed for the detection of SARS-CoV-2 in clinical samples. Some of these assays, especially CDC N1, N2 and N3, and E_Sarbeco have been used to detect SARS-CoV-2 in wastewater samples from the Netherlands (Medema et al., 2020) and USA (Wu et al., 2020) . To the best of our knowledge, this is the first study that reports the detection of SARS-CoV-2 in wastewater samples using the N_Sarbeco assay. In the present study, the N_Sarbeco assay produced positive signals for two wastewater samples, while the same samples were negative when tested using NIID_2019-nCOV_N. It is possible that the N_Sarbeco assay is more sensitive than the NIID_2019-nCOV_N assay. The LOD of the N_Sarbeco assay was 8.3 copies/reaction . As far as we know, the LOD of the NIID_2019-nCOV_N assay is not known. Medema et al. (2020) also noted discrepancies between CDC N1 with CDC N2, CDC N3 and E_Sarbeco assays for several wastewater samples (Medema et al., 2020) . Wu et al. (2020) reported the concentration of SARS-CoV-2 in wastewater samples in Massachusetts, USA using CDC N1, N2 and N3 assays. All three assays produced RT-qPCR quantifiable results with variable levels of SARS-CoV-2 in wastewater samples (Wu et al., 2020) . Another recent study determined the relative performance of the E_Sarbeco, CDC N1, N2, and N3 assays by testing ten nasopharyngeal or oropharyngeal SARS-CoV-2 positive samples. Among the five assays tested, E_Sarbeco and CDC N2 assays were the most sensitive (Nalla et al., 2020) . Vogels et al. (2020) showed that most RT-qPCR assays can be used to detect SARS-CoV-2 by seeding SARS-CoV-2 RNA into RNA extracted from nasopharyngeal swabs, but there are apparent differences in the ability to differentiate between true negatives and positives when concentrations are at or below ten copies/μL of RNA for China CDC N, China CDC ORF1, USA CDC N2, and USA CDC N3 assays. In this study, the level of SARS-CoV-2 in two RT-qPCR positive samples were near the lower limit of detection (i.e, amplified between 37 to 40 cycles). This may have contributed to the inconsistent results between N_Sarbeco and NIID_2019-nCOV_N assays. When the concentration of the target gene, such as SARS-CoV-2 is low, subsampling error may also occur (Taylor et al., 2019) . Therefore, the performance of the currently used assays needs to J o u r n a l P r e -p r o o f be cross validated by seeding SARS-CoV-2 RNA into untreated wastewater samples followed by further inter-laboratory validation. However, we could confirm the specificity of the RT-qPCR by Sanger and MiSeq Illumina Sequencing. Since wastewater is a complex matrix and some assays may produce false positive results, we recommend sequencing RT-qPCR products for confirmation. We used two virus concentration methods because limited information is available on the effectiveness of enveloped virus recovery from wastewater matrices using existing virus concentration methods. The electronegative membrane used in this study is typically used for concentrating enteric viruses from wastewater and environmental waters with modest recovery (Rigotto et al., 2009; Ahmed et al., 2020) . The rationale for using the electronegative membrane is that greater adsorption of enveloped viruses such as mouse hepatitis virus and Pseudomonas phage Φ6 to the solid fraction of wastewater compared to nonenveloped viruses (Ye et al., 2016) . Furthermore, koi herpesvirus (i.e., an enveloped virus) showed high adsorption efficiency to the electronegative membrane (Haramoto et al., 2009) . Besides the electronegative membrane, the Centricon® Plus-70 centrifugal filter has been successfully used to recover SARS-CoV-2 in wastewater samples in the Netherlands (Medema et al., 2000) . A recent study successfully recovered SARS-CoV-2 from wastewater using a polyethylene glycol (PEG 8000) concentration method (Wu et al., 2020) . None of the reported studies to date have provided information on the percent recovery of SARS-CoV-2 from wastewater due to the risk associated with handling SARS-CoV-2 and the requirements for a BSL-3 facility. To the best of our knowledge, only one study has to date reported the percent recovery of SARS-CoV from wastewater which was estimated to be only 1% using an electropositive membrane (Wang et al., 2005) . Since the characteristics of SARS-CoV-2 are different to enteric viruses, more research is needed for the effective recovery of SARS-CoV-2 from wastewater. Little has been documented on the concentration and detection of SARS-CoV-2 in wastewater. Medema et al. (2020) reported binary RT-PCR data, while another recent study reported ~104 copies/100 mL of SARS-CoV-2 in wastewater in Massachusetts, USA (Wu et al., 2020) . The authors acknowledged that the estimated concentration was much greater than the confirmed cases (0.026%). The authors listed several factors and assumptions for this discrepancy and considered their results conservative. The estimated numbers of SARS-CoV-2 in our study were 3-4 orders of magnitude lower than Wu et al. (2020) . In our study, despite only two wastewater samples being RT-qPCR positive, we attempted to provide some quantitative estimation of SARS-CoV-2 in wastewater samples and relate these to the COVID-19 cases in the community. The wastewater surveillance and Monte Carlo data suggest a median SARS-CoV-2 infection prevalence of 0.096% in the catchment basin during the six day period. The clinical prevalence would be equivalent to 450 cases in the catchment, but the upper bound of the 95% confidence interval around the median would suggest up to 764 total cases -314 undiagnosed cases or roughly 7 undiagnosed infections for every 10 diagnosed infections. Unfortunately clinical prevalence data are only available for Queensland at the PHN level, and, therefore extrapolating these to the catchment population is at this stage not possible ( Fig. 1 ) making direct comparisons difficult. Close collaboration with Health Departments will be essential in making these comparisons. Given the current variability and uncertainty in SARS-CoV-2 data, the median is a conservative measure of central tendency that demonstrates reasonable agreement with clinical observations. The model, as currently formulated, is parsimonious with opportunites for refinement as more data become available. Sensitivity analysis indicates localized measures of viral RNA shedding in stool of infected individuals are an important consideration. However, the model does not yet include the proportion of infected patients shedding virus RNA in their stool, since this appears subject to substantial geographic variation -27% in one cohort in China to 88% in a German cohort (Zhang et al., 2020; Wölfel et al., 2020) . The effect of this exclusion would be to increase our estimated prevalence by as much as 4-fold. The model also does not yet include any uncertainty or variation associated with the experimental workflow itself such as recovery of SARS-CoV-2 from wastewater. In regards to the safety aspect of sampling wastewater, we consider that routine safe work practices and PPE have been and continue to be effective in protecting sampling personnel from exposure to pathogens including SARS-CoV-2 (CDC 2020; USEPA 2020). There is no evidence to date that SARS-CoV-2 or the related SARS-CoV-1 has been transmitted via sewerage systems, with or without wastewater treatment (CDC 2020; WHO J o u r n a l P r e -p r o o f 13 2020). Furthermore, initial experiments indicate that faecal loads of SARS-CoV-2 are not infectious (Hennig and Drosten, 2020) . We therefore recommend that future wastewater sampling efforts adhere to established safety procedures. This is a proof of concept study and we have shown that SARS-CoV-2 can be detected in untreated wastewater in Australia. One of the biggest challenges will be to establish  Currently RT-qPCR assays developed for clinical specimen testing are being used for SARS-CoV-2 RNA detection in wastewater samples. Since different assays may produce conflicting results when the concentration is low in wastewater, these assays need to be evaluated head to head in intra-and inter-laboratory studies.  The virus concentration method is another essential factor that requires attention for improving the sensitivity of detection of SARS-CoV-2 in wastewater. 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Hennig Pathogen surveillance through monitoring of sewer systems The ultimate qPCR experiment: Producing publication quality, reproducible data the first time Detection of Novel Coronavirus by RT-PCR in Stool Specimen from Asymptomatic Child Harnessing the power of the census: characterizing wastewater treatment plant catchment populations for wastewater-based epidemiology Analytical sensitivity and efficiency comparisons of SARS-CoV-2 qRT-PCR assays Coronavirus and Drinking water and Wastewater Study on the resistenace of severe acute respiratory syndrome-associated coronavirus Statement on the second meeting of the International Health Regulations (2005) Emergency Committee regarding the outbreak of novel coronavirus (2019-nCoV) Water, sanitation, hygiene, and waste management for the COVID-19 virus Virological assessment of hospitalized cases of coronavirus disease 2019 SARS-CoV-2 titers in wastewater are higher than expected from clinically confirmed cases Authors: medRxiv A new coronavirus associated with human respiratory disease in China Prolonged presence of SARS-CoV-2 viral RNA in faecal samples Wastewater-based epidemiology for early detection of viral outbreaks Fecal specimen diagnosis 2019 Novel Coronavirus-Infected Pneumonia Author's contribution statement Warish Ahmed: Investigation, Resources, Writing Nicola Angel: Resources Janette Edson: Formal analysis, Writing, Investigation Kyle Bibby: Formal analysis Aaron Bivins: Formal analysis, Writing Jake O'Brien: Resources Phil M. Choi: Resources, Writing Masaaki Kitajima: Formal analysis, Writing Stuart Simpson: Resources, Writing Jiaying Li: Resources Ben Tscharke: Resources Rory Verhagen: Resources Wendy J.M. Smith: Resources Julian Zaugg: Formal analysis, Writing Leanne Dierens: Resources Philip Hugenholtz: Resource, Writing, Editing Kevin V. Thomas: Conceptualization, Resources, Writing We thank Amber Migus and Shane Neilson for inspiring this research and providing daily motivations to work faster. Drs Sonja Toft, Jason Dwyer, Paul Sherman (Urban Utlities) for facilitating sample collection and Drs Shihu Hu, Huijuan Li and Shane Watts (Advanced Water Management Center, UQ) for assistance with sample collection. We also thank Laura Leighton (Queensland Brain Institute, UQ) for assistance with gel purification and AGRF for rapid turnaround on the Sanger sequencing results. Our thanks to Margaret Butler and Helen Pennington from the Australian Centre for Ecogenomics for laboratory support.Journal Pre-proof J o u r n a l P r e -p r o o f