key: cord-0834929-sl5nnpd1
authors: Augusto, Matheus Ribeiro; Claro, Ieda Carolina Mantovani; Siqueira, Aline Kaori; Sousa, Guilherme Santos; Caldereiro, Cláudio Roberto; Duran, Adriana Feliciano Alves; de Miranda, Taís Browne; Bomediano Camillo, Lívia de Moraes; Cabral, Aline Diniz; de Freitas Bueno, Rodrigo
title: SAMPLING STRATEGIES FOR WASTEWATER SURVEILLANCE: EVALUATING THE VARIABILITY OF SARS-COV-2 RNA CONCENTRATION IN COMPOSITE AND GRAB SAMPLES
date: 2022-02-26
journal: J Environ Chem Eng
DOI: 10.1016/j.jece.2022.107478
sha: be416a3477d366627e1f6aca9b855d8cc2f6428d
doc_id: 834929
cord_uid: sl5nnpd1

The shedding of SARS-CoV-2 RNA titers by infected individuals, even asymptomatic and oligosymptomatic ones, allows the use of wastewater monitoring to track the COVID-19 spread in a community. This approach is interesting especially for emerging countries with limited clinical testing capabilities. However, there are still important methodological aspects that need validation so that wastewater monitoring data become more representative and useful for public health. This study evaluated the between-day and within-day variability of SARS-CoV-2 RNA concentrations in 24-hour composite and grab samples from three different sampling points, including two wastewater treatment plants (WTTP) and a sewer manhole. In the between-day evaluation (17 weeks of monitoring), a good agreement between the SARS-CoV-2 RNA concentration of each sampling method was observed. There were no significant differences between the mean concentrations of the grab and composite samples (p-value > 0.05), considering N1 and N2 gene assays. The strong relationship between composite and grab samples was proven by correlation coefficients: Pearson's r of 0.83 and Spearman's rho of 0.78 (p-value < 0.05). In within-day evaluation, 24-hour cycles were analyzed and low variability in hourly viral concentrations was observed for three sampling points. The coefficient of variation (CV) values ranged from 3.0 to 11.5%. Overall, 24-hour profiles showed that viral RNA concentrations had less variability and greater agreement with the mean values between 8 a.m. and 10 a.m, the recommended time for grab sampling. Therefore, this study provides important information on wastewater sampling techniques for COVID-19 surveillance. Wastewater monitoring information will only be useful to public health and decision-makers if we ensure data quality through best practices.

an infectious disease [9, [21] [22] [23] [24] . While clinical data provides pooled individual information that is often difficult to interpret, wastewater provides an aggregated sample of an entire area. In addition to reducing monitoring costs, this approach allows the tracking of asymptomatic and oligosymptomatic individuals, who are generally not detected during clinical surveillance [25] [26] [27] [28] .

However, as attested by Shah et al. [29] , the data published so far are insufficient to consolidate SARS-CoV-2 monitoring via wastewater surveillance. There are important methodological aspects to be validated and optimized such as sampling strategies and experimental methods (concentration and quantification of SARS-CoV-2 RNA) [21, 30, 31] . Inaccurate results of wastewater monitoring can lead to harmful decisions and inefficient interventions by authorities [32] .

There are two major sampling methods: time-or flow-proportional composite sampling and grab sampling. A composite sample is a single sample volume constructed of multiple individual samples (aliquots) taken over a specific period. In time-proportional composite sampling, fixed volume aliquots are taken at uniform time intervals during the period of interest. A flow-proportional composite sampling can be performed using two different methods: i) by collecting a constant aliquot volume at varying time intervals proportional to the instantaneous wastewater flow rate; ii) by collecting aliquots of variable volume and proportional to the instantaneous wastewater flow rate, maintaining a constant time interval between the aliquots [33] . Composite sampling, usually performed over 24 hours using manual or autosamplers, is highly recommended in wastewater monitoring. This sampling strategy is less susceptible to the inherent seasonal and diurnal variability of wastewater characteristics, including the viral content J o u r n a l P r e -p r o o f 5 [34] [35] [36] . Several studies have reported the use of composite sampling in SARS-CoV-2 surveillance [10, 11, 13, 26] . However, sampling periods longer than 6 hours have been shown to be unfeasible, especially when it is necessary to collect samples from multiple locations and areas of difficult access (sewer manholes, rivers, among others) [37] .

Furthermore, there is often a need for permanent care of sampling equipment, especially automatic samplers, to prevent theft. Thus, the use of grab sampling can be encouraged in some cases, even though it only represents the conditions of the exact moment of collection.

To date, the study of sampling strategies for SARS-CoV-2 surveillance using wastewater is limited [38] [39] [40] . Curtis et al. [39] found good agreement between the grab samples collected every 2 hours in 72 hours and three corresponding 24-hour flowweighted composite samples. However, the authors suggested avoiding sample collection during periods of low flow and, consequently, of higher concentrations of potential inhibitory substances for PCR reactions. On the other hand, Gerrity et al. [40] verified a 10-fold increase in SARS-CoV-2 RNA concentrations in 24-hour flowweighted composite sampling in comparison to corresponding grab sampling.

Therefore, additional data are necessary for the standardization and validation of the sampling methods [30] .

This study evaluated the variability of SARS-CoV-2 RNA concentrations in composite and grab samples of untreated wastewater from the ABC Region, São Paulo, Brazil.

The differences between the two sampling methods were analyzed in two steps: i) between-day evaluation (17 weeks of monitoring); ii) within-day evaluation (two distinct 24-hour periods). In the second step, three different representative sampling points J o u r n a l P r e -p r o o f were assessed: i) a large-scale wastewater treatment plant (WWTP); ii) a small-scale WWTP; iii) a point in the sewer system (sewer manhole). This study provides important methodological information and insights for future wastewater surveillance research.

The negligence of the sampling technique can greatly increase the uncertainty of monitoring data and, consequently, of COVID-19 prevalence estimates. Assuring data quality is essential to make wastewater surveillance information useful to decisionmakers.

The experiments were performed at three points of the ABC Region, São Paulo, Brazil:

i) a large-scale WWTP; ii) a small-scale WWTP; iii) a point in the sewer system (sewer manhole). Untreated wastewater samples were collected and analyzed for SARS-CoV-2 RNA occurrence. The main information of sampling points is shown in Table 1 . p.m. and 5 a.m. at point 3 (sewer manhole).

Viral particles were concentrated by the precipitation method, as described by Wu et al. [10] . Briefly, 40 mL of samples were centrifuged (8000xg/120 min/4°C) and the pellet J o u r n a l P r e -p r o o f was resuspended in 0.4 mL of 1x PBS (pH 7.2). One milliliter of acid phenol was added and centrifuged (12.000xg/10 min/4ºC) for sample cleaning [13] . The aqueous phase was transferred to a microtube containing 0.3 mL of lysis buffer. RNA extraction was performed using the PureLink™ Viral RNA/DNA Mini Kit (Thermo Fisher Scientific), according to the manufacturer protocol. The final elution volume for the extraction was 80 μL.

To quantify SARS-CoV-2 RNA, reaction mixtures were prepared using the SuperScript™ III One-Step RT-PCR System with Platinum™ Taq DNA Polymerase (Thermo Fischer Scientific, Waltham, MA, USA) for the targeted nucleocapsid (N1 and N2) genomic regions [41] . The enveloped bovine respiratory syncytial virus (BRSV -Inforce™ 3, Zoetis, US) was used for evaluation of concentration methods recovery capacity. The recovery rates were between 20 and 65% [13] . Primers and probes, with sequences and concentrations that are listed in Table S1 , were purchased from Thermo Fisher Scientific. Components of the reaction contained 10 μL 2x reaction mix (0.4mM of each dNTP, 3.2mM MgSO 4 ), 1.5 μL probe and primer mix (FAM-labelled probe, forward and reverse primers), 0.4 μL SuperScript III RT/Platinum Taq mix, 3.1 μL nuclease free-water, 5 μL RNA template to a final volume of 20 μL. RT-qPCR was performed using a CFXOpus 96 thermal cycler (BioRad, Hercules, CA, USA). The thermal cycling conditions for RT-qPCR assays were as follows: initial incubation at 50°C for 30 min and initial denaturation at 95°C for 3 min, followed by 45 cycles of denaturation at 95°C for 3 s, and the primer annealing and extension reaction at 55°C for 30 s (acquiring fluorescence in the green filter).

The RT-qPCR assays for SARS-CoV-2 RNA were performed in duplicates and included negative and positive standard controls. To obtain the standard curves, a 10-fold dilution series of standard RNAs was prepared (2019-nCoV_N_Positive Control Cat.

PC67102, Norgen).

A Calibration curve for N1 (y =-3.407x + 41.619) and N2 (y =-3.510x + 42.733) showed a linear dynamic, as shown in Fig. 1 positive for SARS-CoV-2 RNA, as proposed previously [9, 10] . Following the protocols described by Rajal et al. [42] and Boxus et al. [43] , BRSV RT-qPCR reactions were performed to evaluate the recovery of concentration methods. Recoveries ranging from 20 to 65% were obtained. 

For the data from step 1 (between-day evaluation), prevalence estimates were performed using the SARS-CoV-2 RNA concentration measured in wastewater, considering composite and grab samples, among other parameters, according to the following equations [11, 13, 44] :

Predicted prevalence ( ) N Contri uting population 100 (2) Where:

C RNA = SARS-CoV-2 RNA concentration measured in composite and grab samples (genome copies.L -1 ). F = Wastewater volumetric flow rate (L.d -1 ).

Fecal load (g.person -1 .d -1 ).

SARS-CoV-2 shedding rate by an infected individual (genome copies.g -1 ).

The wastewater volumetric flow rate (F) of point 1 was measured in loco. In the calculations, the average flow rates of the collection days were considered.

The daily fecal mass ( ) produced by humans from low-income countries usually ranges from 75.0 to 520.0 grams per person (with an average value of 243.0 ± 130.2 g.person -1 .d -1 ), according to Rose et al. [45] .

The SARS-CoV-2 shedding rate by an infected individual ( ) usually ranges from 6.3x10 5 to 1.3x10 8 genome copies.g -1 , according to Kitajima et al. [46] and Gholipour et al. [47] .

Thus, the COVID-19 average prevalence was estimated, considering the contributing population of sampling point 1 to be approximately 1,400,000 (Table 1 ).

In step 1 (between-day evaluation), the one-way analysis of variance (ANOVA) was used to determine whether there were differences among the mean SARS-CoV-2 RNA concentrations of each sampling method, considering a significance level of 0.05 (pvalue < 0.05). In addition, descriptive statistics and Pearson's r and Spearman's rho correlation coefficients were used to determine the relationship between the results of composite and grab samplings. As SARS-CoV-2 RNA concentrations in wastewater are log-normally distributed, the statistical analyses were performed with log-transformed data.

The statistical Monte-Carlo approach was incorporated into the calculation of the prevalence estimate (Eq. 1 and Eq. 2) for step 1 data, since parameters such as Fecal load ( ) and SARS-CoV-2 shedding rate ( ) have large variation, which makes it difficult to interpret the results of the infected population (N) and, consequently, the predicted prevalence. The Monte-Carlo simulation was implemented with 10,000 random samplings of the product of and parameters. The parameter was modeled as a normal distribution with mean ± standard deviation of 243.0 ± 130.2 g.person -1 .d -1 , while J o u r n a l P r e -p r o o f the parameter was modeled as a uniform distribution with minimum and maximum values of 6.3x10 5 and 1.3x10 8 genome copies.g -1 , respectively [45] [46] [47] . Statistical analysis were performed using Origin Pro 8.6, while the Monte-Carlo simulation was implemented in Microsoft Excel.

Composite and grab samples of untreated wastewater from point 1 were analyzed between April 14th, 2021 and August 4th, 2021 (113 days) for SARS-CoV-2 RNA occurrence. Samples with Ct (Cycle threshold) less than 40 were considered positive and had their concentrations determined (genome copies/sample volume) [9] .

The RT-qPCR was used to quantify both N1 and N2 gene assays of SARS-CoV-2 RNA in all wastewater samples. The SARS-CoV-2 RNA titers were detected in 88.2% (15/17) and 76.5% (13/17) of composite samples, for N1 and N2 gene assays, respectively, while for the grab samples, the viral genome was detected in 75.0% (12/16) for the two gene assays. In addition to the occurrence percentage, the variability of SARS-CoV-2 RNA concentration for each sampling method was also evaluated ( For the N1 gene assay, lower variability of SARS-CoV-2 RNA concentration was observed in the grab samples, as evidenced by the smaller height of the box (Fig. 2 ).

For the N2 gene assay, the difference in dataset variability was not clear. Table 2 shows the SARS-CoV-2 RNA concentration descriptive statistic of composite and grab samples by gene assay, complementing the information shown in Fig. 2 . As determined by the one-way analysis of variance (ANOVA), there were no significant differences among the mean SARS-CoV-2 RNA concentrations of each sampling method (p-value > 0.05), considering N1 and N2 gene assays. Therefore, there is good agreement between the SARS-CoV-2 RNA concentration of 24-hour composite samples and grab samples.

Differently, Gerrity et al. [40] verified a 10-fold increase in SARS-CoV-2 RNA concentrations in 24-hour composite sampling in comparison to corresponding grab sampling, analyzing primary effluents also from a large WWTP (serving approximately 1 million people). The grab samples of primary effluents corresponded to raw wastewater that arrived at the WWTP between 5 a.m. and 6 a.m., a period of minimum flow rate.

However, as attested by Curtis et al. [39] , periods of minimum flow rate may have higher concentrations of potentially inhibitory substances for PCR reactions. Therefore, prior assessment of the 24-hour variability of viral load in wastewater is recommended to verify the best moment to perform a grab sampling. In this study, after analyzing the Curtis et al. [39] also observed good agreement between SARS-CoV-2 RNA concentration of 24-hour composite samples and grab samples, with a mean deviation of 1590 copies.L -1 . However, unlike the results of this work, the grab sample concentrations were lower than their corresponding composite samples, which can lead to an underestimation of the pandemic severity index. It is worth noting that the study by Curtis et al. [39] was carried out in the early stages of the pandemic, in May 2020, when the accumulated prevalence in the city was approximately 100 cases per 100,000

people. The variation in SARS-CoV-2 RNA is likely to be a function of prevalence. A decrease in variance is expected as the shedding rate increases.

George et al. [48] also found good agreement between SARS-CoV-2 RNA titers There is good agreement between the SARS-CoV-2 viral load of 24-hour composite samples and grab samples (Fig. 3(A) ). Similarly, the estimates of infected individuals (carriers) and prevalence of the two sampling methods also showed good consensus considering their respective confidence intervals ( Fig. 3(B) ).

However, SARS-CoV-2 RNA titers were not detected in the grab samples of weeks 2, 4, 13, and 15, while the corresponding composite samples indicated the occurrence of the virus. Since grab sampling only represents the exact moment of collection, there is a risk of obtaining false negatives and underestimated viral RNA concentrations [34, 49, 50] .

On the other hand, at week 14, the presence of the virus was detected only in the grab sample. In certain cases, the grab sampling can be more beneficial, since the bacteriological and pathogenic samples require immediate analysis due to their instability [34] . However, the positive detection for the grab sample and not for the composite sample could also be explained by the effect of the dilution of subsamples collected during periods of SARS-CoV-2 RNA absence. The observed COVID-19 prevalence (considering epidemiological/clinical data) in the ABC Region for the same period (April 14th, 2021 -August 4th, 2021) ranged from 0.004 to 0.04%, with an average value of 0.02 ± 0.01%. Regardless of the sampling method, the predicted prevalence values were about ten times higher than the reported prevalence. Previously, long-term monitoring (between June 9th, 2020 and April 7th, 2021) of this same sampling site resulted in predicted prevalence values equivalent to this study [13] . Wu et al. [10] in Massachusetts, USA, also found prevalence values (0.1 -5%) higher than those reported from clinical data (about 0.026%). There are many uncertainties in the prevalence estimation model, especially around the SARS-CoV-2 J o u r n a l P r e -p r o o f according to Kitajima et al. [46] and Gholipour et al. [47] . Wölfel et al. [7] indicate that this range may be greater, between 10 2.67 and 10 7.67 genome copies.g -1 . Thus, even using Monte-Carlo statistical simulation, the predicted results may differ from the observed data by more than ten times. Both sampling methods can generate representative and useful results for virus tracking, outbreak prediction, and pandemic monitoring. However, grab sampling must be well designed, considering the previously identified peak periods of fecal loading [34] . It is important to emphasize that, regardless of the sampling technique, it is not possible to determine an absolute concentration of the virus in the wastewater [9, 13] . The relationship between grab and composite sampling data is shown in Fig. 4 . The N1 and N2 data of the positive samples were plotted. Pearson's r and Spearman's rho correlation coefficients were calculated, resulting in 0.83 and 0.78 (p-value < 0.05), respectively. [51] . The two correlation coefficients were similar and lead to the same conclusion that there is a strong and significant linear relationship between the results from the two sampling methods, considering a significance level of 0.05 [52] . The hourly wastewater flow rates were not measured at point 3 (sewer manhole), due to technical difficulties in accessing the sampling site with measuring instruments.

However, the average flow rate was estimated from population data and a per capita wastewater generation of 160 L.person -1 .d -1 , resulting in 4.5 L.s -1 .

As shown in Fig. 5 (C), viral load variability was low, especially for the first period evaluated (day 1), resulting in a CV value of 3.0%. In addition, the presence of the fragments of genetic material of SARS-CoV-2 was not detected in only one of the samples (referring to 21:00 on day 2). This result is very interesting since the monitoring points of the sewer system (sewer manhole) require a more practical sampling strategy.

As discussed, in these sampling sites it is difficult to install autosamplers, for technical and security reasons. Viral RNA concentrations remained relatively stable and close to the average value between 8 a.m. and 11 a.m., for the two periods analyzed. Thus, grab sampling or even 3-hour semi-composite sampling can yield representative results if they are properly planned.

However, George et al. [48] also evaluating low flow sampling sites (flow rates ranging from 0.8 to 7.0 L/s), found high hourly variability in the SARS-CoV-2 RNA titers concentrations and significant differences between grab samples and their respective composite samples. For the ultra-low-flow sampling site (flow rate of 0.8 L/s), the grab J o u r n a l P r e -p r o o f concentrations ranged from 3.44 ± 0.04 to 7.16 ± 0.02 log 10 genome copies.L -1 , while the composite concentration was 5.81 ± 0.08 log 10 genome copies.L -1 . Unlike our observations, George et al. found [48] that the smaller the catchment area, the greater the hourly variability of concentrations and, therefore, the greater the discrepancies between grab and composite samples. track the best timing for grab sampling. PMMoV is an elongated rod-shaped virus with a single-stranded genome that occurs in human feces. In addition to using PMMoV as a marker of fecal contribution, other studies have suggested tracking crAssphage (bacteriophage commonly found in human fecal samples), creatinine (breakdown product from muscle and protein metabolism), and total nitrogen. These markers can be used to normalize sewage strength (fecal content per volume of sewage) [53] .

Another recent study suggested that performing grab sampling during the peak flow rate period could be an interesting approach to SARS-CoV-2 surveillance in wastewater [54] . However, as attested by Ahmed et al. [35] , it is not yet clear if at peak hour of toilet usage we capture the strongest SARS-CoV-2 signal or a more diluted signal.

Furthermore, the travel time of sewage from households to the WWTP can range from 2 to 12 hours or greater, as in the catchment of our study area. There is also the contribution of rainwater and stormwater, which can significantly dilute the RNA titers during the heavy rainfalls. In Brazil, domestic sewage and surface run-off (rainwater and stormwater) are collected separately. However, there are many clandestine connections to the sewer network [13] .

According to The Water Research Foundation [55] , the within-day variation in the concentration of SARS-CoV-2 RNA fragments still remains unknown. In this study, after analyzing the 24-hour variability of SARS-CoV-2 RNA concentrations, we found that the best period to perform grab sampling was between 8 a.m. and 10 a.m. This study presents an important discussion on sampling methods, a step that can be one of the bottlenecks for the effective use of wastewater surveillance. Wastewater samples must be representative to enable the correct diagnosis of the monitored population. Thus, sampling strategies must be carefully evaluated, not only regarding the location of monitoring points and the frequency of collection but also regarding the collection method (composite, grab, and passive). Although composite sampling can provide greater representation, its application requires high financial resources, since in most cases automatic samplers are used. There are many difficulties associated with the use of automatic samplers: i) installation and maintenance costs; ii) availability of equipment; iii) access to the sampling site; iv) safety issues (need for permanent care to prevent theft); v) need for a power supply for refrigerated samplers; and vi) excessive depths at sampling sites, often greater than the capacity of the autosampler pump [61] .

Wastewater sampling methods must balance the objectives of public health and epidemiological surveillance with available financial and human resources. The objective may simply be to detect the presence of SARS-CoV-2 RNA fragments in a population, which will be especially useful after the pandemic ends for monitoring and preventing new outbreaks (early warning system). However, the objective may also be J o u r n a l P r e -p r o o f 31 to quantify the virus in wastewater samples to monitor trends in infection. In this case, the methodological procedures must guarantee greater precision [49] .

Regardless, the results of the present study indicated the possibility of using grab sampling, also ensuring the quality of the generated data. The between-day evaluation showed a high correlation between grab and composite samples, with Pearson's r of 0.83 and Spearman's rho of 0.78 (p-value < 0.05). There were no significant differences among the mean SARS-CoV-2 RNA concentrations of each sampling method (p-value > 0.05), considering N1 and N2 gene assays, as determined by the one-way analysis of variance (ANOVA). The average values of predicted prevalence by Monte-Carlo simulation were 0.2 ± 0.2% and 0.4 ± 0.2% for composite sampling and grab sampling,

respectively.

An absolute comparison between the reported and predicted COVID-19 prevalence is significantly complex [49] . However, as attested by Medema et al. [9] , wastewater surveillance can be used to quickly and cost-effectively monitor infection trends in small or large populations. From the detection and quantification of SARS-CoV-2 RNA titers in wastewater samples, it is possible to create an early warning system [62] .

Wastewater surveillance is a promising and efficient tool with meaningful potential for early warning of outbreaks and infectious disease transmission. By analyzing biomarkers (in this case SARS-CoV-2 RNA) in wastewater sampled at strategic points, disease transmission and spread can be comprehensively monitored in near real-time.

This approach is especially useful for emerging countries with limited economical sources and poor epidemiological surveillance systems.

Several studies on the implementation of wastewater surveillance for COVID-19 have been carried out in different locations around the world. Although the potential of the methodology has already been proven, there are many methodological aspects to be elucidated and optimized. It is essential that all methodological steps are standardized, from the definition of sampling strategies to the detection of genetic material. Only in this way we will be able to generate useful results that complement public health and epidemiological surveillance.

In this context, this research is a step towards the improvement of sampling strategies and, consequently, tracking the spread of SARS-CoV-2 RNA from wastewater samples.

The results presented showed that it is possible to carry out a representative assessment of a population from grab samples. The within-day evaluation showed that the variability of SARS-CoV-2 RNA over the 24-hour cycles should be considered in defining the best sampling time. In this study, the viral RNA concentrations had greater consensus with the mean values between 8 a.m. and 10 a.m. Therefore, prior evaluation of the 24-hour profile of SARS-CoV-2 RNA in wastewater is recommended for proper implementation of grab sampling, as a viable alternative to composite sampling. The particularities of each region and population must be considered.

The authors would like to acknowledge the financial support from the following Brazilian institutions: Brazilian National Council of Scientific and Technological Development

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Aline Kaori Siqueira: Methodology; Writing -review & editing. Guilherme Santos Sousa: Methodology; Data curation; Writing -review & editing. Cláudio Roberto Caldereiro: Methodology; Writingreview & editing

Aline Diniz Cabral: Conceptualization; Methodology; Writing -review & editing. Rodrigo de Freitas Bueno: Conceptualization; Project administration; Resources; Supervision; Writing -original draft. Declaration of Competing Interest ☒ The authors declare that they have no known competing financial interests or personal relationships