key: cord-0768837-3y7fhhg2
authors: Tim, Boogaerts; Lotte, Jacobs; Naomi, De Roeck; den Bogaert Siel, Van; Bert, Aertgeerts; Lies, Lahousse; van Nuijs Alexander, L.N.; Peter, Delputte
title: An alternative approach for bioanalytical assay optimization for wastewater-based epidemiology of SARS-CoV-2
date: 2021-05-26
journal: Sci Total Environ
DOI: 10.1016/j.scitotenv.2021.148043
sha: 04dd80ccfd6116a05ed812081b0ce34f61a1e278
doc_id: 768837
cord_uid: 3y7fhhg2

Wastewater-based epidemiology of SARS-CoV-2 could play a role in monitoring the spread of the virus in the population and controlling possible outbreaks. However, sensitive sample preparation and detection methods are necessary to detect trace levels of SARS-CoV-2 RNA in influent wastewater (IWW). Unlike predecessors, method optimization of a SARS-CoV-2 RNA concentration and detection procedure was performed with IWW samples with high viral SARS-CoV-2 loads. This is of importance since the SARS-CoV-2 genome in IWW might have already been subject to in-sewer degradation into smaller genome fragments or might be present in a different form (e.g. cell debris,…). Centricon Plus-70 (100 kDa) centrifugal filter devices resulted in the lowest and most reproducible Ct-values for SARS-CoV-2 RNA. Lowering the molecular weight cut-off did not improve our limit of detection and quantification (approximately 10(0) copies/μL for all genes). Quantitative polymerase chain reaction (qPCR) was employed for the amplification of the N1, N2, N3 and E -gene fragments. This is one of the first studies to apply digital polymerase chain reaction (dPCR) for the detection of SARS-CoV-2 RNA in IWW. dPCR showed high variability at low concentration levels (10(0) copies/μL), indicating that variability in bioanalytical methods for wastewater-based epidemiology of SARS-CoV-2 might be substantial. dPCR results in IWW were in line with the results found with qPCR. On average, the N2-gene fragment showed high in-sample stability in IWW for 10 days of storage at 4 °C. Between-sample variability was substantial due to the low native concentrations in IWW. Additionally, the E-gene fragment proved to be less stable compared to the N2-gene fragment and showed higher variability. Freezing the IWW samples resulted in a 10-fold decay of loads of the N2- and E-gene fragment in IWW.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is an enveloped non-segmented positivesense RNA virus, which is associated with the pathogenesis of the coronavirus disease 2019 in humans (Huang et al., 2020) . Due to the partly asymptomatic transmission and the high infectivity of this virus Gao, Chen, & Fang, 2020) , it is crucial to have timely and accurate figures on the spread of SARS-CoV-2 in defined population groups for controlling possible viral outbreaks. Currently, the extent of SARS-CoV-2 circulation has been monitored by diagnostic testing of primarily symptomatic patients and contact tracing to also isolate asymptomatic patients (Peccia et al., 2020; Vandamme & Nguyen, 2020) . However, a major limitation with these methods is that they depend on participation of individuals, even when they have no symptoms or only mild aspecific symptoms of COVID-19. Lack of recognition of symptoms or refusal to participate in detection or quarantine measures allows further spread of the virus in the general population. In Belgium, contact-tracing is primarily done manually through regional call centers and through the implementation of a smartphone application. Participation is heavily influenced by personal, social and public trust and requires additional efforts to connect with lower educated and vulnerable population groups (Vandamme & Nguyen, 2020) . Contact-tracing efforts could potentially be biased by reporting and concealment bias and requires from each individual to keep track of their contact list. Additionally, if contacttracers fail to track down an individual's contacts swiftly (for example due to the prolonged incubation period or time to perform diagnostic testing), it could have limited effect on the spread of this highly infectious virus (He et al., 2020) .

Wastewater-based epidemiology (WBE) employs the analysis of influent wastewater (IWW) on human (metabolic) excretion products and has been used as an alternative approach to investigate the circulation and spread of infectious diseases at the population level ( Figure 1 ) (Mao et al., 2020; Sims & Kasprzyk-Hordern, 2020) . Infectious disease biomarkers (e.g. viral genomes) are released, pooled and transported in the wastewater system. The abundance of pathogens in IWW reflects the spatio-temporal changes and spread of number of studies investigate RE through spiking of enveloped surrogate viruses (e.g. coronavirus, the murine hepatitis virus and the bacteriophage pseudomonas virus phi6) Alygizakis et al., 2021; Corpuz et al., 2020; La Rosa, Bonadonna, Lucentini, Kenmoe, & Suffredini, 2020; McMinn et al., 2021; Ye, Ellenberg, Graham, & Wigginton, 2016) . However, even with enteric surrogate viruses, RE of concentrations methods are mostly determined by the virus and the matrix composition. In this light, different coronaviruses (CoV) may have quite distinctive structural and physical properties compared to some of the proposed surrogate viruses and RE observed in these studies may not be representative for SARS-CoV-2 and the structures in IWW that contain SARS-CoV-2 RNA (Haramoto et al., 2018) . Furthermore, it is not exactly known in what complex the SARS-CoV-2 RNA is present in IWW (packaged in virus particles, cellular fragments…) and viral loads may be broken down in smaller fragments during in-sewer transport. We hypothesize that the SARS-CoV-2 RNA is not present as naked RNA due to the poor stability of RNA in IWW. The abovementioned spiking experiments with viruses, although useful, are probably not fully representative for evaluation of stability and extraction of real IWW. In this light, a handful of studies confirmed their presented results in IWW with the native concentrations of SARS-CoV-2 RNA (i.e. concentrations present without seeding the virus to IWW) (Ahmed, Angel, et al., 2020; Hasan et al., 2021; Jafferali et al., 2021; Torii, Furumai, & Katayama, 2021) .

The aim of this study was to compare a broad range of bioanalytical procedures for the concentration of SARS-CoV-2 RNA in IWW. This bioanalytical assay (combination of sample concentration, RNA extraction and PCR detection) was optimized with IWW originating from eight Belgian wastewater treatment plants (WWTPs) with confirmed native levels of SARS-CoV-2 RNA, in combination with spiking with an animal Coronavirus.

Additionally, in-sample stability at different storage conditions was further investigated. Finally, this study applied, as one of the first, digital polymerase chain reaction (dPCR) for assaying SARS-CoV-2 RNA in IWW, in a direct comparison with traditional quantitative polymerase chain reaction (qPCR).

company that had a high number of positive COVID-19 cases (approximately 17% of the employees) (Outters, 2020) . Daily IWW samples were collected in the preamble (2 nd of August 2020), peak (20 th of November 2020) and tail (20 th of January 2021) of the second wave of the COVID-19 pandemic. Locations are not further specified due to anonymity constraints, however, matrix compositions differ substantially between the locations of interest to demonstrate the robustness of the methodology. Additionally, catchment areas with distinctive geographical characteristics (e.g. cities versus towns) were considered to test the suitability of the bioanalytical method. Although it is virtually impossible to determine the broad range of matrix interferences present in IWW, matrix compositions will vary significantly between days and locations due to spatio-temporal differences in disposal and excretion of compounds in the sewer system (Corpuz et al., 2020) . It should be noted that in-sewer degradation in the SAW could potentially be less substantial compared to the IWW samples because of minor average hydraulic residence times at the subcatchment level . Previously, Choi et al. indicated that biotransformation of WBE biomarkers could be substantial due to the influence of hydrochemical parameters and presence of biofilms .

SARS-CoV-2 RNA decay could potentially be more substantial during in-sewer transport due to the presence of biofilms and hydrochemical processes, as indicated by Ahmed et al .

Additionally, the SARS-CoV-2 genome is more diluted in IWW compared to the SAW, which could result in different decay rates .

For method optimization, the applicability of the sample concentration and extraction methods was tested in IWW from the second wave of the COVID-19 pandemic in Belgium where the number of positive test cases was substantial. This period was deliberately chosen for the assessment of suitability of the method because higher number of test cases will result in higher excretion of SARS-CoV-2 RNA. Additionally, the samples acquired during the preamble and tail of the COVID-19 pandemic also demonstrate the applicability of the method in Virus concentration is necessary because of the low levels of SARS-CoV-2 RNA in wastewater. The analytical procedure needs to be sensitive enough to detect viral loads in the beginning or at the tail of the COVID-19

peak when only a limited number of SARS-CoV-2 infections are present in the catchment area. Several ultrafiltration methods (for protocols, see figures S1-S2) with different centrifugal devices with varying molecular weight cut-offs (MWCO) and loading volumes were tested for the concentration of viral RNA loads in IWW in order to obtain high extraction efficiencies. Additionally, PEG precipitation was also tested as an alternative for sample concentration. Conditions of the PEG precipitation (e.g. initial volume, final concentration of PEG and NaCl,…) were given in Figure S3 . It should be noted that co-concentration of PCR inhibitors could also occur when using these concentration methods which could affect the assay's sensitivity . The composition of the IWW matrix is highly variable and contains a range of heavy metals, RNases and polysaccharides that could interfere with qPCR amplification (Corpuz et al., 2020; Gibson et al., 2012) . It is logistically impossible to determine the exact composition of the collected IWW samples, however, due to the complexity of the IWW matrix it is highly expected that substances present in IWW will result in some degree of inhibition.

Several studies are already available addressing different methods for concentrating viruses in wastewater through spiking the IWW samples pre-and post-extraction with a surrogate control virus Alygizakis et al., 2021; Corpuz et al., 2020; . However, the complex of the SARS-CoV-2 RNA present in IWW (virus particles, cellular fragments, etc.) remains uncertain and for the amplification of the different SARS-CoV-2 gene fragments was chosen for sample concentration. This approach was chosen since spiking IWW with enteric enveloped viruses may not be representative for RE of SARS-CoV-2 RNA in IWW due to different structural properties of these surrogate viruses or the in-sewer degradation of viral SARS-CoV-2 genome. However, during method optimization, IWW samples were spiked in parallel with porcine coronavirus (PRCV) to investigate whether the RE of this seeded surrogate control virus was in line with the SARS-CoV-2 results when optimizing the different concentration protocols. Table 1 summarizes the design of experiment with the varying extraction protocols in order to obtain the most suitable sample concentration method of viral RNA loads in the wastewater matrix. In the final protocol, samples were firstly centrifuged at 4625g for 30 minutes at 4 °C to remove solids and debris. The supernatans was transferred to a Centricon Plus-70 centrifugal filter for sample concentration. The sample was centrifuged for 15 minutes at 2500g at 4 °C in these ultrafiltration devices. Subsequently, the filter cup was centrifuged for an additional 2 minutes at 1000g at 4 °C to collect the sample concentrate. Finally, the sample concentrate was extracted and standardized at a volume of 1.5 mL.

Similar to the sample concentration protocols, different commercially available manual RNA extraction kits were compared in order to obtain the lowest and most reproducible Ct-values for both SARS-CoV-2 and PRCV. concentration of the primer and probes in the different qPCR mixtures was given in Table 2 . A six-point calibration curve with a concentration between 10 5 and 10 0 copies/µL was constructed in ultrapure DEPCtreated water for quantification of the different gene fragments of interest in IWW. The lower limit of quantification (LLOQ) was defined as the concentration in the lowest point of the calibration curve and was 10 0 copies/µL for all gene fragments. All qPCR reactions were performed in duplicate. For each qPCR run, two negative controls and a positive control were included. qPCR settings were as follows: 10 minutes for reverse transcription at 45 °C, 2 minutes at 95 °C for polymerase activation followed by 45 cycles of 5 seconds at 95 °C for denaturation and 30 seconds at 60 °C for annealing and extension. Concentrations (in copies/µL) were only considered in this study (i) when comparing the results measured in this study with the results found by others, (ii) when comparing the performance of qPCR and dPCR and (iii) when assessing in-sample stability. The same sample concentration and RNA extraction method was applied to compare qPCR with dPCR and to assess insample stability allowing the use of this metric.

concentrations of SARS-CoV-2 RNA in the sewer system. The aim of the in-sample stability experiments was to determine suitable storage conditions for the collected IWW samples.

IWW samples from the eight different locations with substantial viral RNA loads were divided in multiple aliquots of 50 mL and stored at different temperatures (4 °C and -20 °C). These aliquots were subsequently analyzed with the final sample preparation protocol (as described above) at different time points for all gene fragments of interest, as illustrated in Figure 2 . Important to note is that all aliquots stored at -20 °C were only thawed once at the moment of analysis. The effect of multiple freeze-thaw cycles was not considered in this study. However, it has to be mentioned that multiple freeze-thaw cycles could lead to extensive breakdown of SARS-CoV-2 RNA by RNases present in IWW.

For each IWW sample, viral loads for each gene fragment were quantified at each time point and expressed as a relative percentage of the native concentration present in the corresponding IWW samples at the starting point of this stability study. The mean and relative standard deviation (%RSD) of all IWW samples were considered for each gene fragment of interest. Figure S4 , as illustrated in Figure 3A . Overall, increasing the sample volume resulted in the lowest Ct-values for the gene fragments of interest with the different sample concentration methods. However, higher loading volumes (i.e. two times the maximum capacity of the filter) often resulted in blockage of the centrifugal filter membrane and, therefore, the IWW sample was only loaded once to prevent this. Blockage of the filter could also potentially lead to higher concentrations of PCR-inhibitors which could negatively influence the sensitivity with qPCR. The use of lower sample volumes also increases the throughput of the bioanalytical assay, since higher loading volumes require multiple centrifugation steps.

Lower MWCO did also not result in more sensitive detection of SARS-CoV-2; only the Amicon centrifugal filters with a MWCO of 10 kDa showed minor improvements. Although only two different MWCO were tested for each of the individual filters, results were consistent for all centrifugal devices (with the exception of the Amicon filters). Larger MWCO could also potentially result in minimizing co-concentration of PCR inhibitors.

Concentration with the Centricon Plus-70 centrifugal filters resulted in the lowest Ct-values; the other centrifugal filters were comparable. It is hypothesized that the Centricon Plus-70 centrifugal filters are potentially more suitable due to a higher RE, a higher concentration factor and less co-concentration of PCR inhibitors, but more research is needed to confirm this hypothesis. Other studies also found acceptable RE of surrogate viruses or seeded SARS-CoV-2 in IWW with some of these ultrafiltration methods. Loading volumes ranged between 50 and 500 mL in these studies. However, the variation of the RE with these sample J o u r n a l P r e -p r o o f Journal Pre-proof concentration methods was quite substantial Alygizakis et al., 2021; .

The color of each cell represents the Ct-value, the y-axis the different sample concentration protocols and the x-axis the different PCR assays. Cells indicated with a red asterisk have higher Ct-values than the lowest point of the calibration curve and could therefore not be quantified. However, in these cells a positive signal was still detected.

Structural properties of the SARS-CoV-2 RNA found in the SAW might differ from the viral loads measured in IWW due to in-sewer degradation of viral RNA during sewage transport. It should be noted that only one SAW sample was acquired from the corresponding company, however, performance of the different centrifugal filters was in line with the results in Figure S4 . Although the effect of different MWCO was consistent throughout the different filters, it should be noted that the small sample size is a limitation for the interpretation of these results. Figure S4 compares the different RNA extraction protocols for both SARS-CoV-2 and PRCV. The use of the Powermicrobiome kit resulted in low detection levels of the different SARS-CoV-2 gene fragments in IWW.

Therefore, this RNA extraction method was excluded at an early stage. The Viral RNA and RNeasy extraction kit showed comparable results, with slightly higher detection levels observed with the Viral RNA extraction kit for both SARS-CoV-2 and PRCV. Concentration factors were similar between both kits (Table S1 ), but slightly higher compared to the Maxwell PureFood GMO and Authentication kit and the Powermicrobiome kit. The Viral RNA extraction kit also recovered higher viral RNA loads in frozen IWW compared to the RNeasy extraction kit. However, in frozen IWW viral loads were almost always lower than the LLOQ, as further discussed in section 3.4. Additionally, the effect of diluting IWW samples with ultrapure water was also taken into consideration to evaluate the tolerance of dPCR to matrix interferences. Positive IWW samples from three locations were either:

(i) not further diluted, (ii) diluted with a factor of 2 or (iii) diluted with a factor of 4 before sample concentration. The same diluted IWW samples were analysed with qPCR to provide a comparison between both assays. The results presented in Table S4 illustrate that diluting the samples with qPCR resulted in poor detection levels for the different gene fragments. Diluting the IWW samples with a factor of 2 resulted in improved sensitivity with dPCR. This could potentially indicate that dPCR is more tolerant to matrix interferences compared to qPCR. It should be noted that the dilution factor was taken into account when calculating the concentrations presented in Tables S3 and S4 . This experiment and the results shown in Table 3 potentially highlight the usefulness of dPCR for the wastewater-based epidemiology of SARS-CoV-2, however, the presented results should be further verified with larger sample sizes and IWW originating from other locations with distinct matrix compositions. A calibration curve prepared from the same RNA extracts was processed with both qPCR and dPCR. A major advantage of dPCR is that it allows absolute quantification and, thus, no calibration curve is needed. The different calibration points were amplified with dPCR as a proxy to validate variability at different concentration levels and Ct-levels with qPCR. This is of importance because native concentrations of SARS-CoV- Figure 5 combines the result for the calibration curve observed with qPCR with the results of dPCR. At low concentration levels (10 -1 to 10 0 copies/µL), the width of the CI tends to be rather broad. For the E-gene fragment, no positive partitions were measured in the reaction well containing the 10 0 copies/µL calibration point. The width of the CI for the N1-and N2-gene fragment at this concentration level was 79.0% and 95.7%

respectively (see also Table S2 ). This further evidences the high variability observed at Ct-values around the LLOQ with qPCR and could potentially explain why only one single well out of the side-by-side duplicates tested positive for SARS-CoV-2. Of course, the high variability observed in WBE applications for SARS-CoV-2 has further implications for the analysis of temporal trends in SARS-CoV-2 infections, especially in catchment areas with low prevalence of COVID-19. This uncertainty is further explored in section 4. The N2-gene fragment and E-gene fragment were detected in concentrations above the LLOQ in 100% and enhance the accuracy and precision of WBE for SARS-CoV-2. This also further emphasizes the need for surrogate CoV (e.g. PRCV) as whole process control to ensure overall quality of these bioanalytical assays. The presence of a whole process control is especially of importance because of the high variability in the composition of the matrix. The fraction of PCR inhibitors could vary within a single WWTP over time and is potentially very different between WWTPs. In this study, the %RSD at the low detection levels was still considerable, as indicated with dPCR. The high variability observed in the LLOQ range also addresses the need for replicates.

To our knowledge, limited information is available on the in-sewer degradation of the SARS-CoV-2 genome with only Ahmed et al. investigating in-sewer stability through the use of microcosm experiments . This study showed acceptable persistence of SARS-CoV-2 RNA in untreated wastewater at 4 °C and 15 °C for several days, which is generally much higher than the hydraulic retention times in wastewater collection systems. However, this was tested in the absence of biofilms and may therefore not be representative of different sewer structures. Low to medium stability can severely impact the concentration of the SARS-CoV-2 RNA in IWW. Additionally, fragmentation of the genome during in-sewer transport could potentially affect RE with the different concentration methods found in literature and lead to high variation between WWTPs due to different sewer structures and presence of biofilms Kitajima et al., 2020) . In the future, sequencing of the SARS-CoV-2 genome in IWW is required to identify the different fragments of the SARS-CoV-2 genome in IWW. This would add valuable information on the state of SARS-CoV-2 RNA in IWW.

In the final protocol, solids were removed during the pre-centrifugation of the IWW samples. However, adsorption of the SARS-CoV-2 genome to the pellet could affect RE. In this study, SARS-CoV-2 was detected to some extent in solids (data not shown), but the overall importance needs to be further explored.

The present study proposes an alternative approach to assess RE of SARS-CoV-2 gene fragments in IWW with different ultrafiltration protocols. Native concentration levels of the different SARS-CoV-2 gene fragments measured in IWW from different Belgian WWTPs with the different sample concentration methods were used to optimize RE of SARS-CoV-2 RNA in IWW. The bioanalytical assay proved to be capable of measuring low J o u r n a l P r e -p r o o f Journal Pre-proof concentrations of SARS-CoV-2 RNA present in the samples from different IWW sources. The present study is among the first to apply dPCR for the quantification of SARS-CoV-2 RNA in IWW and dPCR results were comparable with the qPCR results.

The variability observed with the sample concentration methods for SARS-CoV-2 remains substantial due to the lack of an 'ideal' external control standard with similar properties to SARS-CoV-2. This control standard would also be able to robustly correct for differences in matrix composition between days and locations. At this moment, there is also a lot of uncertainty regarding the state of SARS-CoV-2 genome (fragments) in IWW due to potential in-sewer degradation. More research on variability of SARS-CoV-2 in IWW and potential transformation of SARS-CoV-2 RNA in the IWW is necessary to further investigate the applicability of WBE.

Although WBE can already aid in filling some critical knowledge gaps in the epidemiological surveillance of SARS-CoV-2, future research should aim to further validate and standardize bioanalytical assays, especially with regards to methodological uncertainties. This is especially of importance when the number of WBE applications on data triangulation with other epidemiological information sources outpace the number of WBE studies that investigate intrinsic methodological uncertainties.

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The funding of this project was obtained from the Research Council (BOF) of the University of Antwerp [project number: FFB200184] and the Agency of Care and Health [project number: GE0-1GPFZJA-WT]. Additionally, we thank Sciensano and the personnel of Aquafin for their support in collection of the IWW samples. We also would like to acknowledge Prof. H. Nauwynck (Ghent University, Merelbeke, Belgium) and Prof. K. Ariën