key: cord-0292036-3k5mcjih
authors: Yanac, K.; Adegoke, A.; Wang, L.; Yuan, Q.; Uyaguari, M.
title: Detection of SARS-CoV-2 RNA Throughout Wastewater Treatment Plants and A Modeling Approach to Understand COVID-19 Infection Dynamics in Winnipeg, Canada
date: 2021-10-28
journal: nan
DOI: 10.1101/2021.10.26.21265146
sha: 92cf5dc86411735394357bd94beb9c4926a22f14
doc_id: 292036
cord_uid: 3k5mcjih

Although numerous studies have detected SARS-CoV-2 in wastewater and attempted to find correlations between the concentration of SARS-CoV-2 and the number of cases, no consensus has been reached on sample collection and processing, and data analysis. Moreover, the fate of SARS-CoV-2 in wastewater treatment plants is another issue, specifically regarding the discharge of the virus into environmental settings and the water cycle. The current study monitored SARS-CoV-2 in influent and effluent wastewater samples with three different concentration methods and sludge samples over six months (July to December 2020) to compare different virus concentration methods, assess the fate of SARS-CoV-2 in wastewater treatment plants, and describe the potential relationship between SARS-CoV-2 concentrations in influent and infection dynamics. Skimmed milk flocculation (SMF) resulted in higher recoveries of an internal positive control, Armored RNA, and higher positivity rate of SARS-CoV-2 in samples compared to ultrafiltration methods employing a prefiltration step to eliminate solids. Our results suggested that SARS-CoV-2 may predominate in solids and therefore, concentration methods focusing on both supernatant and solid fractions may result in better recovery. SARS-CoV-2 was detected in influent and primary sludge samples but not in secondary and final effluent samples, indicating a significant reduction during primary and secondary treatments. SARS-CoV-2 was first detected in influent on September 30th, 2020. A decay-rate formula was applied to estimate initial concentrations of late-processed samples with SMF. A model based on shedding rate and new cases was applied to estimate SARS-CoV-2 concentrations and the number of active shedders. Inferred sensitivity of observed and modeled concentrations to the fluctuations in new cases and test-positivity rates indicated a potential contribution of newly infected individuals to SARS-CoV-2 loads in wastewater.

scraped using a sterilized spatula, and the remaining pellets in the tubes were 169 resuspended in 250 µL of 0.2M sodium phosphate buffer with a pH 7.5 (Alfa Aesar, 170 Ottawa, ON, Canada) and transferred to 1.5 mL Eppendorf tubes. 171 Recovery Efficiency: Total recovery for ultrafiltration and SMF method workflows 172 were determined by spiking 5x10 4 copies of Armored RNA Quant IPC-1 Processing 173 Control (Asuragen, Austin, TX, USA) (Alygizakis et al., 2021; Eveleigh et al., 2019;  174 Hietala and Crossley, 2006) into six raw wastewater samples from North End is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 2.4. In this study, N1 and N2 primers/probe sets (Integrated DNA Technologies, Inc., 195 Coralville, IA, USA), each targeting a different region of the Nucleocapsid (N) gene of 196 SARS-CoV-2 (CDC, 2020), were used. Each 10-μl RT-qPCR mixture consisted of 10 197 μl of 2.5 µL of 4X TaqMan Fast Virus 1-Step Master Mix (Life Technologies, 198 Carlsbad, CA, USA), 400 nM each primer, 250 nM probe, 2.5 μl of the template and 199 ultrapure DNAse/RNAse free distilled water (Promega Corporation, Fitchburg, WI, 200 USA). Calibration curves for quantifying N1 and N2 specific assays were obtained 201 using six 10-fold dilutions (ranging from 2.0 to 2.0E+05) of the 2019-202 nCoV_N_Positive Control plasmid DNA (Integrated DNA Technologies, Inc., 203 Coralville, IA, USA). Armored RNA was quantified using 10-fold dilutions of synthetic 204 single-stranded DNA (Integrated DNA Technologies, Inc., Coralville, IA, USA). 205 Primers and probe sets (Integrated DNA Technologies, Inc., Coralville, IA, USA) used 206 to detect and quantify the Armored RNA are given in Table S3 . Calibration curves 207 were obtained for each RT-qPCR run. Negative controls were also included in each 208 qPCR run. Thermal cycling reactions were performed at 50 °C for 5 minutes, followed The concentration of SARS-CoV-2 in wastewater in Winnipeg was normalized by 214 dividing daily total SARS-CoV-2 load in wastewater by the total daily wastewater flow 215 rate (eqn. 1). The normalization was implemented for the three WWTPs using eqn. 1, 216 where NC is normalized concentration, C represents the SARS-CoV-2 concentration, 217 and WF indicates the daily wastewater flow. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 Where Ct is the concentration at time t, Co represents the initial concentration, and k 236 indicates the decay rate. A log-linear model was derived from eqn. 2 for the back-237 calculation of N1 and N2 concentrations (gene copies) as shown in eqn. 3, where Ct 238 is the concentration of N1 or N2 genes at time t, C0 is the initial concentration of N1 239 or N2 genes at the sampling day, k is the decay rate of N1 or N2 genes, and t is the 240 delay in processing the samples. (Gerrity et al., 2021; Wölfel et al., 2020) . The ascertainment ratio was assumed as 2 254 . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.

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The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101 doi: medRxiv preprint (Gerrity et al., 2021) , which means the model will multiply the number of cases by 2.

Instead of assuming a constant daily wastewater flow rate, we used daily wastewater 256 flow rates provided by the city of Winnipeg. Based on the shedding rate and 257 shedding decay rate, an infected person is expected to shed SARS-CoV-2 for 26 258 days with a burst on the initial days of infection. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101/2021.10.26.21265146 doi: medRxiv preprint ( Fig. 1 ). After getting negative or weak SARS-CoV-2 genetic signals in wastewater 279 samples with UF-7.5K x g, further recovery experiments were conducted to 280 determine recovery efficiency at 7500 x g, and but Armored RNA was not recovered. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 SMF was later employed to concentrate and detect SARS-CoV-2 in wastewater 291 samples. Using Armored RNA as a control, 15.27% ± 3.32% of recovery was 292 achieved from the spiked wastewater samples (Fig. 1.) . SMF has the highest 293 recovery efficiency with the smallest standard deviation whereas UF-7.5K x g has the 294 lowest recovery efficiency with 5 negative samples out of 6 samples.This method did 295 not employ a prefiltration step with cheesecloth and low-protein binding 0.45 and 0.2 296 µm 47-mm membrane filters. Therefore, the losses due to the elimination of solid 297 particles were minimized and might have been reflected through the higher 298 percentage and lower variation in recovery. Percent recovery values for SMF were 299 comparable to the recovery values reported by Philo et al. (2021) . They also reported 300 30% positivity rate for SARS-CoV-2 with SMF. Table 3 shows concentrations of SARS-CoV-2 in wastewater and sludge samples 306 collected during the sampling period. Three different concentration methods, namely 307 UF-3K x g, UF-7.5K x g and SMF, were applied (Fig. 2 ). UF-3K x g and UF-7.5K x g 308 methods required a prefiltration step with 0.45 and 0.2 m filters to eliminate the 309 effects of solids on ultrafiltration performance and separate viral fraction from 310 bacterial fraction. On the other hand, SMF did not require any prefiltration step, and 311 therefore SARS-CoV-2 particles on solids were also concentrated with this method.

All influent and effluent samples were processed using UF-3K x g method (Fig. 2) .

Influent samples collected between October 28 th and December 15 th were processed 314 with both UF-3K x g AND UF-7.5K x g methods. They were first concentrated with 315 . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.

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The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101/2021.10.26.21265146 doi: medRxiv preprint UF-7.5K x g method, and the negative samples were further processed with UF-3K x 316 g method within 4 days of sampling. As samples were negative when processed with 317 UF-3K x g and UF-7.5K x g methods between November 16 th and December 15 th 318 ( Fig. 2) , SMF method was applied delayed (Table 1) is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101/2021.10.26.21265146 doi: medRxiv preprint et al., 2021b), losses during virus concentration (Chik et al., 2021; Ye et al., 2016) , 331 losses during extraction, and PCR related issues, such as inhibition and incomplete 332 reverse transcription (Bustin et al., 2009 ). Since the variables in this study were the is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. (Table 4 ) when total solids concentrations were higher in the 398 samples collected from NESTP between October 28 th and November 18 th (Table S4) .

This increase can be attributed to the increase in total solids due to the partitioning of 400 SARS-CoV-2 to solid phase (Chik et al., 2021) . The relationship between case data 401 (Fig. 3) and SARS-CoV-2 concentration in solids during this period should not be 402 overlooked, as discussed in section 3.2.4. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint samples were processed with UF-3K x g and UF-7.5K x g methods. However, SARS-CoV-2 was detected in these samples using SMF (Fig. 2 and Table 3 ), although the sample processing was delayed between 46 and 75 days (Fig. 2) . is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101/2021.10.26.21265146 doi: medRxiv preprint limited, the current findings point out the predominant partition of SARS-CoV-2 to solid phase and higher stability of SARS-CoV-2 in solids. The results of this study, together with previous studies (Chik et al., 2021; Hokajärvi et al., 2021a; Markt et al., 2021) , underscores the importance of the inclusion of both solids and supernatant fractions in wastewater processing for the detection of SARS-CoV-2. However, adsorption capacity of SARS-CoV-2 to wastewater solids needs to be investigated.

Both N1 and N2 genomic targets of SARS-CoV-2 were detected in all primary sludge samples collected from NESTP and SESTP while they were not detected on November 16 th , and only N2 was detected on November 18 th and December 1 st in the samples collected from WESTP (Table 3 ). The input volume of primary sludge samples processed for the detection of SARS-CoV-2 in this study was only 300 L, which is much lower than the input volumes in previous studies (Graham et al., 2021; Peccia et al., 2020) . Still SARS-CoV-2 was detected, indicating the high density of SARS-CoV-2 in primary sludge. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101/2021.10.26.21265146 doi: medRxiv preprint primary sludge density of 3.53 ± 0.84 % and was generally the lowest in the samples collected from WESTP with an average sludge density of 0.37 ± 0.06 % (Table S5) .

This statement assumes homogeneous distribution of prevalence and incidence throughout the city of Winnipeg on the sampling days based on the high correlation between influent viral concentrations in WWTPs (r>0.91 for N1 and r>0.72 for N2) (Table S6 ). Higher input volumes should be considered for consistent and sensitive detection and quantification of the viral RNA in sludge samples. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

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SARS-CoV-2 was not detected in both secondary and final effluent samples of all three WWTPs (Table 3) , although it is worth mentioning that WESTP employs solar disinfection, which effectively reduces bacteria and is questionable in removing viruses, especially in cold climate conditions (Parsa et al., 2021) . Employing UV disinfection, NESTP and SESTP might have effectively reduced SARS-CoV-2 concentration below detectable levels in final effluent. SARS-CoV-2, being an enveloped virus, is expected to be more sensitive to disinfection processes (UV, ozonation, and chlorination) than non-enveloped viruses (Chen et al., 2021; Saawarn and Hait, 2021) . Non-detection of SARS-CoV-2 in tertiary-treated effluent samples was also reported elsewhere (Randazzo et al., 2020; Sherchan et al., 2020) , indicating the efficacy of disinfection processes in the removal of SARS-CoV-2 considering high positivity rates (>83 %) in influent samples. This claim was further supported by the occurrence of SARS-CoV-2 in secondary-treated effluent (before disinfection) samples Randazzo et al., 2020) . SARS-CoV-2 is removed not only by disinfection processes but also primary and secondary treatment processes, which can also effectively reduce SARS-CoV-2 concentration in the WWTPs (Balboa et al., 2020; Randazzo et al., 2020; Sherchan et al., 2020) is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 SARS-CoV-2 in WWTPs and the effects of virus concentration methods and input volume on the detection and quantification of SARS-CoV-2 in effluent samples. and 6 to 24 times (Havers et al., 2020) higher than reported cases in the U.S. A study by Hong et al. (2021) focusing on the estimation of the minimum number of SARS-CoV-2 infected cases for the detection of viral RNA in wastewater estimated a minimum number of active cases of 253 to 459 positive cases per 10,000 population to detect SARS-CoV-2 in wastewater, which is much higher than the number of active cases on the day of the first detection in Winnipeg considering the population of Winnipeg (766, 900) (Winnipeg, 2021) .

However, the reported range of active cases needed for the detection of SARS-CoV-. CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.

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The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101/2021.10.26.21265146 doi: medRxiv preprint 2 might be a system-or site-specific estimation since the detection of SARS-CoV-2 in wastewater depends on many factors, including sampling frequencies, concentration methods, and their recovery efficiencies, RT-qPCR detection performance, sample size, daily wastewater flow rates (dilution factor), and environmental factors which can affect the persistence and abundance of SARS-CoV-2 in wastewater (Hong et al., 2021) . Moreover, new cases predominantly contribute to the concentration of SARS-CoV-2 in wastewater rather than active cases (Gerrity et al., 2021; Wu et al., 2022) due to higher viral shedding rates in the very early stages of the infection (Benefield et al., 2020; He et al., 2020; Wei et al., 2020; Wölfel et al., 2020) .

Therefore, the number of active cases, without the data regarding new and earlystage cases, may not be enough in determining the minimum number of cases to detect SARS-CoV-2 in wastewater.

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The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10. 1101 The difference between symptom onset and test confirmation suggests that time-lag might be another explanation for the detection of SARS-CoV-2 when the number of active cases was low. There is also a typical 4 to 5 day incubation period before onset of the symptoms (He et al., 2020; Li et al., 2020) . A possible effect of time-lag can be further confirmed by the sharp increase in the number of cases and five-day test positivity rate (Fig. 3) after September 30 th . Between the first sampling date, July 8 th , and September 30 th , the five-day test positivity rate fluctuated between 0.0% and 3.0 % (Fig. 3) (Manitoba, 2021) . On September 30 th , the test positivity rate was 2.1 %, and henceforth a constant increase in the test positivity rate until mid-December was noticed, with a peak test positivity rate of 14.2 % on December 14 th . During this period, we detected SARS-CoV-2 in all influent samples (including solids fractions) collected from three wastewater treatment plants, except on October 28 th (Table 3) , using different concentration methods.

Previous studies have reported associations between the concentration of SARS-CoV-2 in primary settled solids and COVID-19 cases (Graham et al., 2021; Peccia et al., 2020) . In this study, SARS-CoV-2 was detected in almost all primary sludge samples. In the previous sections, the fluctuations in the concentration of SARS-CoV-2 were partly associated with total solids in the samples. A direct correlation between concentrations and reported cases is intentionally avoided due to low-resolution is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 volumes could generate more reliable and consistent results for a wastewater surveillance study.

Using reported decay rates for N1 and N2 gene fragments Hokajärvi et al., 2021a) Peak concentrations of SARS-CoV-2 were observed on the day when critical-level restrictions were enforced and the following 4 th and 6 th day (Fig. 4) . Other observed concentrations after the first detection were generally in close proximity with the modeled concentrations for at least one genomic target. Different decay rates for N1 and N2 resulted in higher concentrations of N1 for back-trajectory modeled samples collected between November 16 th and December 15 th, while the difference between N1 and N2 concentrations for the rest of the samples was smaller than 0.35 on log10 scale (Fig. 4) . The decay rate of N1 was calculated based on the degradation of genomic signals of gamma-irradiated SARS-CoV-2 by Ahmed et al. (2020b) and had a higher standard deviation of 15% and lower R 2 of 0.79 compared to those values of N2, which were based on degradation of active SARS-CoV-2 (Hokajärvi et al., 2021a) (Table 2) . Gamma irradiation of SARS-CoV-2 and relatively higher variations . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.

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The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 in the decay rate of N1 might result in significant biases in such a back-trajectory modeling approach. Therefore, we mostly consider N2 concentrations for backtrajectory modeled samples in the discussion. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 ascertainment ratio of 2. Blue circles represent modeled shedding cases in Winnipeg, i.e. modeled active cases.

The critical level restrictions in Manitoba were applied when extensive community transmission of COVID-19 occurred, outbreaks could not be controlled, and a heavy toll on the health-care system is expected. With the enforcement of the restrictions on November 12 th , gatherings and travels were extremely restricted, and schools and non-essential businesses were closed. Bearing in mind that the outbreak and transmission are at the critical levels when the restrictions are applied, the occurrence of a much higher number of new cases compared to reported numbers is most likely because of the limited testing capacity at the peak times and time-lag between the incubation period of SARS-CoV-2, onset of the symptoms and test confirmation (He et al., 2020; Li et al., 2020) . In this study, such a scenario was validated with the observed concentrations of SARS-CoV-2 in influent that peaked following the enforcement in November and significantly lowered to the modeled concentrations in December as the outbreak was contained. The difference between the observed concentrations of N2 and modeled concentrations (0.79 to 0.97 on log10 basis) in November suggests that the actual number of cases might be much higher than reported numbers, which is further supported by the sharp increase in testpositivity rates and the number of new cases (Fig. 3) . These findings correspond to the findings of Havers et al. (2020) , reporting that the actual number of cases can be as high as 24 times of reported numbers.

In general, observed concentrations were sensitive to the fluctuations in test-positivity rates and the number of new cases except for the samples collected in November.

Model 2 assumed an ascertainment ratio of 2, which is an optimistic assumption considering ascertainment ratios up to 24 in the literature (Havers et al., 2020; is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10. 1101 .10.26.21265146 doi: medRxiv preprint al., 2020 . While an ascertainment ratio of 2 in the model generated comparable concentrations with the observed concentrations for September, October, and December samples, a higher ascertainment ratio might come into question during the peak times in November. The high concentrations and ascertainment ratios in November can be explained by the high transmission rates of the disease and the number of asymptomatic and presymptomatic cases around this period. After the enforcement of critical level restrictions, public mobility and disease transmission were expected to be minimized. However, the number of new cases and the testpositivity rate remained high during the sampling in November and December, most likely due to time-lag associated with the peaking of viral load and disease transmissivity prior to symptom onset (Benefield et al., 2020; He et al., 2020; . Probably most individuals were infected around the first day of the enforcement but developed symptoms later, which was in agreement with the typical incubation period of 4-5 days before symptom onset Lauer et al., 2020; Li et al., 2020) , and only sought healthcare and underwent testing after symptom onset. SARS-CoV-2 load in December might be due to prolonged shedding from individuals infected earlier. Additionally, individuals infected before the enforcement can infect other people living with them in subsequent days, and disease transmission can still be high among essential workers and their families after the enforcement.

Estimation of SARS-CoV-2 concentration based on shedding rate and reported cases has been previously studied with an emphasis on the significant contribution of newly infected individuals to SARS-CoV-2 loads in wastewater and occurrence of the highest fecal shedding rates in the first days of infection before symptoms develops and tests are conducted (Gerrity et al., 2021; Wu et al., 2022) . They also reported . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.

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The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10. 1101 high similarity between the observed and modeled concentrations, which validates the efficacity of such models to estimate concentration and infection dynamics.

Sensitivity of SARS-CoV-2 levels in wastewater to the fluctuations in the number of new cases and test-positivity rates in this study suggest that an initial burst of viral shedding may occur in the very early stages of COVID-19 infection even before symptom onset and may be followed by a prolonged period of lower shedding rates up to 30 days as reported by Chen et al. (2020) , Hoffmann and Alsing (2021), Wölfel et al. (2020) and (Wu et al., 2022) .

Our data suggest that a back-trajectory model as a function of decay rate and time may be used to estimate initial concentrations of late processed samples as it fit the modeled concentrations and fluctuations in new cases. High-resolution sampling and site-specific decay rates may help to validate and improve the model. Time-lag, testing capacity, and test-positivity rates in addition to the reported cases and shedding rate should also be considered for the shedding rate-based models to obtain better model fits and estimations.

Wastewater surveillance of COVID-19 has been considered an early-warning tool for potential outbreaks and an informative method to characterize COVID-19 infection dynamics. However, researchers have not reached a consensus on sample collection and processing, and data analysis. Furthermore, the potential discharge of SARS-CoV-2 from wastewater treatment plants to the environment is another issue that requires a comprehensive investigation of the fate of SARS-CoV-2 throughout the wastewater treatment process. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 The current study focused on the detection of SARS-CoV-2 in wastewater and sludge samples and the relationship between detection and infection dynamics in Winnipeg. Our results showed that SARS-CoV-2 might predominate in solids. Concentration methods focusing on supernatant and solids fractions may perform better in virus recovery, especially for enveloped viruses. Thus, the type of concentration method may significantly affect SARS-CoV-2 recovery from influent samples.

SARS-CoV-2 might be substantially removed during primary and secondary treatment as SARS-CoV-2 was detected in influent and primary sludge but not in secondary and final effluents. The high affinity of SARS-CoV-2 to solids and detection of SARS-CoV-2 in primary sludge samples at high concentrations suggest sludge line as a potential removal mechanism and a sampling spot for wastewater surveillance. Improvement in processing sludge samples for viral concentration and detection is required to gain more insight into the fate of SARS-CoV-2 in sludge line and optimize sampling and processing.

In addition to the detection and fate of SARS-CoV-2 in WWTPs, the proposed study underlines the relationship between SARS-CoV-2 levels in influent samples and infection dynamics characterized by increasing COVID-19 incidence and prevalence during the sampling period. Both observed and modeled concentrations were sensitive to the fluctuations in new cases and test-positivity rates, suggesting an early burst of viral shedding in infected individuals. During the peak times, the number of infections can be much higher than the number of reported cases considering the time-lag between infection and test confirmation, and asymptomatic infections. To confirm our findings and improve such shedding rate-based models, additional studies with higher sampling resolution and the models informed by some other factors factors, such as time-lag, test capacity, and test-positivity rates, are required. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted October 28, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 Overall, this study demonstrates that SARS-CoV-2 may predominate in solids, and wastewater surveillance of COVID-19 can provide valuable insights into infection dynamics prior to clinical test confirmations.

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

Decay of SARS-CoV-2 and surrogate murine hepatitis virus RNA in untreated wastewater to inform application in wastewater-based epidemiology

Comparison of virus concentration methods for the RT-qPCR-based recovery of murine hepatitis virus, a surrogate for SARS-CoV-2 from untreated wastewater

Analytical methodologies for the detection of SARS-CoV-2 in wastewater: Protocols and future perspectives

Effect of selected wastewater characteristics on estimation of SARS-CoV-2 viral load in wastewater

The fate of SARS-CoV-2 in WWTPs points out the sludge line as a suitable spot for monitoring. medRxiv

Evaluation of viral concentration methods for SARS-CoV-2 recovery from wastewaters

SARS-CoV-2 viral load peaks prior to symptom onset: a systematic review and individual-pooled analysis of coronavirus viral load from 66 studies. medRxiv

Household Transmission of SARS-CoV-2: Insights from a Population-based Serological Survey. medRxiv

Wastewater-based epidemiology pilot study to examine drug use in the Western United States

Monitoring human enteric viruses in wastewater and relevance to infections encountered in the clinical setting: a one-year experiment in central France

Persistence of SARS-CoV-2 in Water and Wastewater

The MIQE Guidelines: Minimum Information for Publication of Quantitative Real-Time PCR Experiments

Development and application of a one-step low cost procedure to concentrate viruses from seawater samples

Making Waves: Coronavirus detection, presence and persistence in the water environment: State of the art and knowledge needs for public health

The presence of SARS-CoV-2 RNA in the feces of COVID-19 patients

Comparison of approaches to quantify SARS-CoV-2 in wastewater using RT-qPCR: Results and implications from a collaborative inter-laboratory study in Canada

Quantitative analysis of SARS-CoV-2 RNA from wastewater solids in communities with low COVID-19 incidence and prevalence

Covid-19: identifying and isolating asymptomatic people helped eliminate virus in Italian village

Municipal Wastewater Surveillance Revealed a High Community Disease Burden of a Rarely Reported and Possibly Subclinical Salmonella enterica Serovar Derby Strain

Using Armored RNA®/DNA as Reliable Molecular Controls in Infectious Disease Testing and Beyond

Early-pandemic wastewater surveillance of SARS-CoV-2 in Southern Nevada: Methodology, occurrence, and incidence/prevalence considerations

SARS-CoV-2 RNA in Wastewater Settled Solids Is Associated with COVID-19 Cases in a Large Urban Sewershed

Persistent viral shedding of SARS-CoV-2 in faeces -a rapid review

First environmental surveillance for the presence of SARS-CoV-2 RNA in wastewater and river water in Japan

Detection and quantification of SARS-CoV-2 RNA in wastewater and treated effluents: Surveillance of COVID-19 epidemic in the United Arab Emirates

Seroprevalence of Antibodies to SARS-CoV-2 in 10 Sites in the United States

Temporal dynamics in viral shedding and transmissibility of COVID-19

Armored RNA as virus surrogate in a real-time reverse transcriptase PCR assay proficiency panel

SARS-CoV-2 known and unknowns, implications for the water sector and wastewater-based epidemiology to support national responses worldwide: early review of global experiences with the COVID-19 pandemic

Faecal shedding models for SARS-CoV-2 RNA amongst hospitalised patients and implications for wastewater-based epidemiology. medRxiv

The detection and stability of the SARS-CoV-2 RNA biomarkers in wastewater influent in Helsinki

The detection and stability of the SARS-CoV-2 RNA biomarkers in wastewater influent in Helsinki

Estimating the minimum number of SARS-CoV-2 infected cases needed to detect viral RNA in wastewater: To what extent of the outbreak can surveillance of wastewater tell us

COVID-19: in the footsteps of Ernest Shackleton

Environmental Surveillance for Poliovirus and Other Enteroviruses: Long-Term Experience in Moscow

Shedding of SARS-CoV-2 in feces and urine and its potential role in person-to-person transmission and the environment-based spread of COVID-19

SARS-CoV-2 in wastewater: State of the knowledge and research needs

The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application

Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia

Detection and stability of SARS-CoV-2 fragments in wastewater: Impact of storage temperature. medRxiv

Identification of multiple potential viral diseases in a large urban center using wastewater surveillance

Presence of SARS-Coronavirus-2 in sewage. medRxiv

Presence of SARS-Coronavirus-2 RNA in Sewage and Correlation with

Prevalence in the Early Stage of the Epidemic in The Netherlands

Environmental surveillance of poliovirus in sewage water around the introduction period for inactivated polio vaccine in Japan

Viral load of SARS-CoV-2 in clinical samples

Effectiveness of solar water disinfection in the era of COVID-19 (SARS-CoV-2) pandemic for contaminated water/wastewater treatment considering UV effect and temperature

Measurement of SARS-CoV-2 RNA in wastewater tracks community infection dynamics

A comparison of SARS-CoV-2 wastewater concentration methods for environmental surveillance

SARS-CoV-2 RNA in wastewater anticipated COVID-19 occurrence in a low prevalence area

Occurrence, fate and removal of SARS-CoV-2 in wastewater: Current knowledge and future perspectives

First detection of SARS-CoV-2 RNA in wastewater in North America: A study in Louisiana

Effect of storage conditions on SARS-CoV-2 RNA quantification in wastewater solids

Urban wastewater analysis as an effective tool for monitoring illegal drugs, including new psychoactive substances, in the Eastern European region

Making waves: Wastewater surveillance of SARS-CoV-2 for population-based health management

A comprehensive method for amplicon-based and metagenomic characterization of viruses, bacteria, and eukaryotes in freshwater samples

Presymptomatic Transmission of SARS-CoV-2 -Singapore

Detection of SARS-CoV-2 in raw and treated wastewater in Germany -Suitability for COVID-19 surveillance and potential transmission risks

Population of Winnipeg

Virological assessment of hospitalized patients with COVID-2019

SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases

Substantial underestimation of SARS-CoV-2 infection in the United States

Municipal Wastewater as a Microbial Surveillance Platform for Enteric Diseases: A Case Study for Salmonella and Salmonellosis

Survivability, Partitioning, and Recovery of Enveloped Viruses in Untreated Municipal Wastewater

We thank the City of Winnipeg, the management, and operators at the NESTP, SESTP, and WESTP for collecting samples and providing information regarding wastewater characteristics, in particular Jong Hwang, Brendan Hellrung, Mark Lefko, Jorge Martins, and Shaun Walker. We acknowledge Ms. Shana Mann and Miss Jocelyn Zambrano (University of Manitoba) for nucleic acid extraction from solids. We also thank Tri Le (University of Manitoba) for proofreading.