Wastewater surveillance has played a pivotal role in monitoring SARS-CoV-2 transmission worldwide. However, developing and implementing the methods underpinning these programmes in regions with prolonged periods of low community transmission has proven challenging. In Victoria, Australia, wastewater surveillance provided early warning of unknown community infections and informed timely public health decisions to limit their spread when case numbers were low. To achieve this, we developed a methodological approach sensitive to extremely low viral loads and could readily identify false positives within short turnaround times. Here, we describe the successful development, implementation, and evaluation of analytic methods using Reverse Transcriptase Quantitative Polymerase Chain Reaction (RT-qPCR) and amplicon sequencing in tandem with CRISPR DETECTR in an ongoing, large-scale surveillance programme to detect SARS-CoV-2 in wastewater in Victoria, Australia. Our study covers ten months, from July 2020 to April 2021, and includes all state-wide health districts and prolonged periods with no known, active community cases among the ∼6.7 million population.

  • A fully operationalised wastewater monitoring programme for SARS-CoV-2.

  • Multi-tiered strategy enabling application during periods of low to zero SARS-CoV-2 transmissions.

  • Readily verifiable RT-qPCR results with precision and pace using amplicon sequencing and CRISPR assay.

  • Potential to adapt to wastewater surveillance of novel, emerging, or re-emerging infections.

Following the discovery of SARS-CoV-2 in December 2019 and during the emergence of the Coronavirus disease 2019 (COVID-19), efforts to limit viral transmission relied heavily on social distancing, masking, and contact tracing. However, observations that SARS-CoV-2, such as SARS-CoV (Chan et al. 2004) and MERS-CoV (Corman et al. 2016), was shed in faeces (Xu et al. 2020) raised questions about its detectability in wastewater and whether detections reflected community transmission (Medema et al. 2020a). Early studies readily detected SARS-CoV-2 in wastewater, even when known infection rates were as low as 1 per 100,000 population (Medema et al. 2020b). Many subsequent studies have described the detection of SARS-CoV-2 in wastewater networks and have provided critical support for SARS-CoV-2 control worldwide (Cervantes-Avilés et al. 2021; Hamouda et al. 2021; Amman 2022; Brunner et al. 2023; Haver et al. 2023; Yousif et al. 2023).

During the acute phase of the COVID-19 pandemic, wastewater surveillance programmes for SARS-CoV-2 heavily relied on RT-qPCR methods repurposed from clinical testing (Kitajima et al. 2020) performed on population-level samples from wastewater catchments. For most of the pandemic, viral caseloads were consistently high in many areas of the world, and these methods performed well (La Rosa et al. 2020; Radu et al. 2022) and typically focused on providing forewarning of a major change in community transmission (Gonzalez et al. 2020; Ahmed et al. 2021; Castiglioni et al. 2022; Radu et al. 2022). In Australia, before late 2021, the situation was starkly different, with community transmission vastly lower than much of the rest of the world. During this time, most Australian states had periods of weeks or months without recording active cases other than in incoming travellers. This was despite widespread access to and uptake of Polymerase Chain Reaction (PCR) testing, as well as screening of high-risk cohorts. In that context, wastewater surveillance emerged as a valuable public health tool, offering the potential for early warning of unknown cases in a geographic area and facilitating the targeted and timely identification of infected individuals prior to substantive community transmission could occur (Ahmed et al. 2021; Black et al. 2021).

Here, we describe the development (before 25 August 2020) of a robust wastewater surveillance programme for SARS-CoV-2 in Victoria, Australia, and its implementation (25 August 2020, onwards) into a state-based surveillance programme. Our study focuses on samples collected from 6 July 2020, to 16 April 2021, which included prolonged periods with low to no known community cases. Due to the low rate of known SARS-CoV-2 cases in the state over this period, the primary focus of the wastewater surveillance programme was to detect unknown community cases and provide a timely and reliable warning system for the Victorian public.

Two major challenges were presented by implementing the surveillance programme during this time. First, the surveillance method had to amplify trace viral amounts at the limit of RT-qPCR detection to minimise false-negative test results. In practice, this meant running a high number (45) of RT-qPCR amplification cycles and considering trace and single-gene detections at a fluorescent cycle threshold >40 as potential positives, which contradicted the manufacturer's advice (PerkinElmer, USA) for detecting SARS-CoV-2 in clinical samples. This requirement created the second major challenge. Increasing detection sensitivity to minimise false negatives typically reduces diagnostic specificity but also increases false positives, and since hundreds of wastewater samples were tested in the Victorian programme per month, often with few expected true positive detections, the risk of producing false positive results was high. Even a 1–2% false-positive detection rate would have rendered the programme ineffective and potentially undermined community trust in public health leadership.

To ensure decisions regarding public health actions could be made confidently, ambiguous RT-qPCR results required validation. This was achieved by amplicon sequencing and a CRISPR DNA endonuclease-targeted CRISPR Trans Reporter method (DETECTR)-based assay (Chen et al. 2018). Although sequencing SARS-CoV-2 obtained from wastewater was not novel, other researchers tended to focus on variant identification (Martin et al. 2020; Crits-Christoph et al. 2021), whereas our focus was on developing a rapid presence/absence confirmation with high sensitivity and specificity. The CRISPR DETECTR assay (Chen et al. 2018) was introduced to produce same-day confirmations reliably. Together, these methods provided an integrated strategy demonstrating how similar surveillance programmes can adapt to emerging threats and conditions of low community transmission where sensitivity and specificity are equally important.

Sample sites, collection protocols, and storage

All sampling for the present study occurred within Victoria, Australia, from 6 July 2020 to 16 April 2021. Different sampling/collection methods were used if the collection point was raw sewage influent at wastewater treatment plants (WTP) or within network sewage flow. Raw wastewater samples were collected as 250 mL grab or composite raw water, as described previously (Black et al. 2021), from a total of 161 sites, representing influent from 74 WTP throughout Victoria, Australia, as well as wastewater pumping stations and network sites located within large WTPs in the metropolitan cities of Melbourne and Geelong (details in Supplementary Table S1). Additional network sampling was conducted by continuous deployment for variable periods (i.e., daily to weekly basis) of 3D-printed passive samplers fitted with electronegative membranes (47 mm diameter, 0.45 μm pore size, cellulose nitrate electronegative membrane (Sartorius, Germany); [see Schang et al. (2021)]) at 104 sites across metropolitan Melbourne, supplemented by grab/composite sampling at some sites (details in Supplementary Table S1). Each sample was transported on ice or in a cold pack and held in the laboratory at 4 °C for no more than 24–48 h before analysis.

Viral purification and extraction

Raw wastewater samples were processed as per Ahmed et al. (2020) and Black et al. (2021), employing MgCl2 (final concentration of 25 mM) salting and filtration through a 0.45 μm and 47 mm electronegative membrane (Sartorius, Germany) using a vacuum manifold. Before 16 July 2020, 100 mL was filtered per sample. After that date, the volume of sample processed was reduced (ranging from 5 to 50 mL) to limit the concentration of substances that inhibit the downstream RT-qPCR assay (details in Supplementary Table S1).

Raw wastewater samples collected before 24 August 2020 were either processed on the same day or stored at −80 °C for up to 72 h until analysis. The Ribonucleic Acid (RNA) extracts from these samples were also stored at −80 °C for up to 72 h until further analysis. In contrast, all samples collected after 24 August 2020 were processed the same day or within 18 h of receipt to minimise any potential loss of viral materials from freezing. Wherever possible, the RNA extracts from these later samples were processed on the day of the extraction to minimise RNA degradation due to freezing. Total RNA was extracted from the whole membrane using the MagMAX™ Microbiome Ultra Nucleic Acid Isolation Kit (Thermo Fisher Scientific, USA) on a KingFisher™ Duo Prime robotic workstation (Thermo Fisher Scientific), with a modified lysis step as per Black et al. (2021).

All passive samplers were cleared of external debris upon arrival in the laboratory and dismantled. The internal electronegative membrane swabs were collected and retained. Where possible, passive samplers were processed for RNA extraction immediately upon receipt. However, if passive samplers were received late and dismantled on the same day, the membranes were frozen overnight at −80 °C. If a passive sampler could not be dismantled on the day of delivery, it was kept at 4 °C overnight, dismantled the next morning, and immediately processed for RNA extraction. For passive samples collected prior to 7 November 2020, RNA extraction was undertaken using the RNeasy® PowerMicrobiome® kit (QIAGEN, Germany) or NucleoSpin RNA Stool isolation kits (Mackerey-Nagel, Germany), the latter as per Schang et al. (2021). After 7 November 2020, all passive samples were processed for RNA extraction using the NucleoSpin RNA Stool isolation kits (Mackerey-Nagel, Germany), as per Schang et al. (2021).

RT-qPCR-based detection

RNA extracts were analysed using the PerkinElmer® SARS-CoV-2 Nucleic Acid Detection Kit (RUO) as per Black et al. (2021) and Schang et al. (2021) at a maximum of 45 RT-qPCR cycles. Each RNA extract was spiked with 10 μL of the MS2 bacteriophage internal positive control as supplied in the PerkinElmer SARS-CoV-2 Nucleic Acid Detection Kit (RUO) (PerkinElmer, USA), and RT-qPCR inhibition was calculated as per Black et al. (2021) and Schang et al. (2021). Inhibited samples (i.e., as per MS2 internal control) were re-run at 1:10 or 1:33 dilutions, as per Schang et al. (2021). This kit is a multiplex assay including primers and Taqman probes targeting a region within the N gene and ORF1ab locus of the SARS-CoV-2 genome overlapping with those amplified by the CCDC-N and CCDC-Orf1ab primer pairs (Kitajima et al. 2020) and an unspecified region of the MS2 genome. The total reaction volume for all RT-qPCRs for the duration of the study was 30 μL. However, the template volume was refined during the programme development stage (before 25 August 2020) before a stabilised method was deployed for all subsequent testing (details in Supplementary Table S1). These changes in template volume were undertaken to maximise sensitivity and limit RT-qPCR inhibition.

All samples were run with a negative RT-qPCR control (non-template control, or NTC) prepared using the Tris-EDTA (TE) buffer provided by the manufacturer. Gamma-irradiated SARS-CoV-2 was used as a positive RT-qPCR control, and five dilutions of the Twist synthetic SARS-CoV-2 RNA control 1 (GenBank ID: MT007544.1, Cat no: 102019) were used for the quantitative standard curve. The limit of detection (LOD) and limit of quantification (LOQ) were determined by Black et al. (2021) and Schang et al. (2021) using gamma-irradiated SARS-CoV-2 RNA and Twist Synthetic RNA Control 1. The LOD was defined by analysing 10 replicates for each dilution of the Twist Synthetic RNA Control 1. The lowest number of copies of the N gene and Orf1ab gene detected in 80% of the samples was found to be 1 copy/mL of wastewater for both targets (Black et al. 2021). LOQ was determined to be 1.8 copies/mL, corresponding to Cq = 40.3 for the N gene and Cq = 39.3 for Orf1ab gene (Schang et al. 2021). Genome equivalents (or viral copy numbers) were estimated using the average Cq values from two technical replicates and calculated based on the mean intercepts and slope for the N gene (intercept = 43.6, slope = −3.47) and the Orf1ab gene (intercept = 42.5, slope = −3.38) generated from standard curves (Schang et al. 2021). The cycle threshold was manually adjusted to detect all amplification signals observed on the multicomponent plot. The baseline was also manually adjusted between cycle three and two to three cycles before the first amplification signal was observed. Samples processed before 16 July 2020 were run using the Applied Biosystems™ 7500 real-time PCR system (Thermo Fisher Scientific, USA). After 16 July 2020, all PCR assays were run on a Bio-Rad CFX-96 Deep Well Real-Time PCR Detection System (Bio-Rad Laboratories, USA). To verify that wastewater detections of SARS-CoV-2 obtained by RT-qPCR were true positives, we employed amplicon sequencing and rapid CRISPR DETECTR genotyping.

Result confirmation by amplicon sequencing

The N and Orf1ab amplicons generated by RT-qPCR were sequenced to differentiate true from false-positive SARS-CoV-2 detections. As the RT-qPCR amplicons generated by the PerkinElmer assay were too short (99 bp for N and 119 bp for Orf1ab) to be practical for Sanger sequencing and incorporated with poor efficiency into an Illumina short-read sequencing library (data not shown), the libraries were prepared using a modified overhang-extension PCR protocol (see Supplementary Method 1 for details). Briefly, PCR primers were evaluated against control RNA material from gamma-irradiated SARS-CoV-2 viruses (data not shown) and were then used in a two-phase PCR protocol to extend the amplicons at their 5′ and 3′ ends by adding synthetic oligonucleotide sequences previously assessed against the Wuhan reference SARS-CoV-2 genome (NC_045512) to ensure no significant sequence complementarity. Library construction was completed by adding index barcodes before sequencing on an Illumina MiSeq (Illumina, USA). The reads were demultiplexed using the paired F and R index barcodes and analysed using a custom Geneious Prime® (version 2020.2.2) pipeline.

Result confirmation by CRISPR DETECTR

From 6 October 2020, the CRISPR DETECTR method (Chen et al. 2018) was used as a rapid companion to confirm the identity of N and Orf1ab amplicons identified by RT-qPCR (see Supplementary Method 2 for details). Briefly, amplicon-specific Cas12a-guideRNAs were designed against the N and Orf1ab sequences (Supplementary Figure 1A and 1B) per the manufacturer's instructions: N-guide RNA – CTGCTGCTTGACAGATTGAACCA and Orf1ab-guide RNA-1 – CACATACCGCAGACGGTACAGAC for the Orf1ab amplicon. An ssDNA-fluorescently quenched (FQ) reporter (/56-FAM/TT TTT TTT T/ZEN/T TT/3IABkFQ/) was added to the reaction mixture. When the Cas12a-guideRNA (i.e., CTGCTGCTTGACAGATTGAACCA for the N amplicon and CACATACCGCAGACGGTACAGAC for the Orf1ab amplicon) detects the sequence of interest, the DNase activity of Cas12a is initiated, cleaving the target DNA proximal to a short T-rich (TTTV, TTCV, or CTTV) protospacer-adjacent motif site (Chen et al. 2018). Next, the surrounding ssDNA-FQ reporter is degraded, and a quantifiable fluorescent (FAM reporter dye and ZEN/3′Iowa Black quencher dye) signal is detected. Results were analysed using CLARIOstar software, and graphs were plotted using Prism9 software. In June 2021, a new Orf1ab-guide RNA (AAAACACAGTCTGTACCGTC) was designed to differentiate the full-length (119 bp) Orf1ab amplicon from an apparent amplification artefact (Supplementary Figure S1B, also see the ‘Results’ Section for details). This redesigned Orf1ab-guide RNA was used to confirm the identity of all Orf1ab amplicons identified by RT-qPCR from 8 June 2021.

Result interpretation using a multi-tier strategy

The surveillance programme was implemented using a multi-tier strategy that included a conservative decision matrix for timely reporting of wastewater detections. The matrix, which sought to account for the potential uncertainty of the results while maximising assay sensitivity and positive predictive value, was refined over time based on the data (Figure 1). A false-positive test was considered to have occurred if an RT-qPCR amplicon could be sequenced and confirmed as arising from a source other than SARS-CoV-2. RT-qPCR positive samples that could not be sequenced or confirmed by other means were considered unconfirmed and inconclusive rather than false positives.
Figure 1

A multi-tier strategy (or decision matrix) at key stages and tiered response was adopted for the wastewater surveillance programme in Victoria, Australia. The matrix illustrates the detection status and confirmation process for SARS-CoV2, including possible detection (Tier 0) and confirmed detections (Tiers 1, 2, or 3). The matrix also highlights the additional quality control and independent testing performed for presumptive detections (Tier non-zero). The primary method for independent confirmation involves sequencing and/or CRISPR.

Figure 1

A multi-tier strategy (or decision matrix) at key stages and tiered response was adopted for the wastewater surveillance programme in Victoria, Australia. The matrix illustrates the detection status and confirmation process for SARS-CoV2, including possible detection (Tier 0) and confirmed detections (Tiers 1, 2, or 3). The matrix also highlights the additional quality control and independent testing performed for presumptive detections (Tier non-zero). The primary method for independent confirmation involves sequencing and/or CRISPR.

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Data visualisation and statistical analysis

Data visualisation and statistical analysis were performed using functions available in R version 3.6.2 (R Core Team 2021) and the R package ‘tstools’ version 0.3.8 (Bannert et al. 2022).

Victorian COVID cases (6 July 2020–16 April 2021)

Victoria is Australia's second most populous state (∼6.7 million people), including the Melbourne metropolitan area (∼5.1 million population) and regional towns, cities, and areas spanning ∼227,000 km2. Over the study period from 6 July 2020 to 16 April 2021, Victoria conducted 4.65 million clinical tests for SARS-CoV-2 and recorded 17,668 known infections (Supplementary Table S2). Of these known cases, 17,087 occurred between 7 July and 15 September 2020. During this period, the mean rate of daily and total active cases was 3.3 and 61.5 per 100,000 population, respectively, peaking at 10.6 daily infections per 100,000 population on 5 August 2020, and 122.4 active cases per 100,000 population on 11 August 2020. From 16 September 2020 to 16 April, 2021, Victoria had an average of 0.04 and 1.3 daily active cases per 100,000 population, respectively. Over the 284-day study period, there were 104 days on which Victoria recorded no new infections 65 days over which the state had no known active cases in the community or hotel quarantine, and numerous additional days in individual catchments, particularly outside the Melbourne metropolitan area. Periods without active cases occurred from 12 November to 11 December 2020, and from 11 March to 14 April 2021.

Sample collection and RT-qPCR detection

From 6 July 2020 to 16 April 2021, 6,802 wastewater samples were collected for testing for SARS-CoV-2 in Victoria. Of these, 869 (12.8%) were collected as 24-h composites, 3,784 (55.6%) as grab samples, and 2,149 (31.6%) as passively collected samples (Supplementary Table S1). Although ∼70% (4,804) of all samples were collected within metropolitan Melbourne (population ∼5,000,000), repeat sampling was conducted across all ten health districts in Victoria, covering most of the state's wastewater infrastructure and catchment population (Supplementary Tables S3–S6). In total, 396 samples produced an RT-qPCR amplicon in either the nucleocapsid (N) gene or the Orf1ab assay (Table 1). Of these, 137 were identified as SARS-CoV-2 positive at quantifiable levels (Cq < 39) in both assays. A further 136 were quantitatively positive by N and 84 by Orf1ab only (Table 1). Thirty-nine samples had late amplification (Cq > 40) in both assays below the quantitative threshold. No amplification was observed in the NTCs.

Table 1

RT-qPCR test results for N and Orf genes for different sample types (values in the bracket indicate mean N and Orf copies or viral copies per mL or per passive sampler)

Sample type (%)RT-qPCR positive (N and Orf1ab)N onlyOrf1ab onlyBoth n.q.Rt-qPCR negative (N and Orf1ab)
Composite (12.8%) 51 (49.4, 94.9) 35 (24.7) 18 (7.1) 761 
Grab (55.6%) 57 (21.4; 39) 54 (20.39) 52 (4.8) 31 3,590 
Passive (31.6%) 29 (529.8; 255) 47 (556.1) 14 (182.1) 2,055 
Total (100%) 137 136 84 39 6,406 
Sample type (%)RT-qPCR positive (N and Orf1ab)N onlyOrf1ab onlyBoth n.q.Rt-qPCR negative (N and Orf1ab)
Composite (12.8%) 51 (49.4, 94.9) 35 (24.7) 18 (7.1) 761 
Grab (55.6%) 57 (21.4; 39) 54 (20.39) 52 (4.8) 31 3,590 
Passive (31.6%) 29 (529.8; 255) 47 (556.1) 14 (182.1) 2,055 
Total (100%) 137 136 84 39 6,406 

Note. The breakdown of each sample type is shown in brackets as a percentage. Symbol: n.q; non-quantifiable.

Dual-target positive samples had the highest estimated viral loads, with means of 34.6 and 65.4 viral copies per mL of raw water based on N and Orf1ab, respectively, and means of 414.6 and 266.5 viral copies per sampler for passive samples (Table 1 and Supplementary Table S1). Although the mean estimated viral copies per mL per raw water sample were nearly two-fold higher for the Orf1ab than the N assay, these numbers appeared to be heavily influenced by a subset of outlier samples. On a sample-by-sample basis, 51 of the dual-target positive raw water samples had a higher estimated viral load based on the Orf1ab assay; for the remaining 57 samples, the N assay gave a higher estimate. Notably, all outlier water samples were tested before September 2020, while the RT-qPCR methods for the programme were still being optimised. This corresponded to a change from storing extracted RNA for up to 72 h at −80 °C before PCR testing to storing it at 4 °C for testing within 24 h. Thus, the discrepancy between N and Orf1ab-based quantitation before September 2020 may result from RNA degradation that impacted N copy numbers more heavily. This is consistent with advice from the kit manufacturer (Perkin Elmer, pers. comm.) but has not, to our knowledge, been systematically verified. The mean estimated viral loads of single-target positive samples were lower than the dual-target samples, at 22.0 and 5.3 viral copies per mL of raw wastewater and 556.1 and 182.1 per passive sampler, based on N or Orf1ab, respectively (Table 1 and Supplementary Table S1).

From a temporal perspective, positive SARS-CoV-2 wastewater detections were highest in the 3 months spanning July (86%), August (65%), and September (34%) 2020 (100 samples collected per month, on average), which coincided with the peak period of COVID reported cases in Victoria over the study period (Figure 2 and Supplementary Figure 4; Supplementary Tables S1, S2, S7–S10). These months also coincided with the highest mean estimated viral loads per sample, at 46.3 and 57 viral copies per mL of raw wastewater based on the N gene and Orf1ab, respectively (Supplementary Table S1, Figure 2, and Supplementary Figure 4). In contrast, from October 2020 to March 2021, positive SARS-CoV-2 wastewater detections were only 4.7% on average, and the mean estimated viral load for SARS-CoV-2-positive samples tested from October 2020 to April 2021 was 11.96 and 7.64 viral copies per mL of raw wastewater and 502.1 and 239.0 viral copies per passive sampler for the N and Orf1ab genes, respectively (Supplementary Table S1, Figure 2, and Supplementary Figure 4).
Figure 2

Active COVID-19 cases (seven-day average) in Victoria, Australia (source: covid19data.com.au/Victoria), during the outbreak (a) and post-outbreak (b) and the corresponding monthly mean (horizontal bar within each box plot) SARS-CoV-2 (N gene and Orf1ab gene) copies were detected from wastewater samples collected using composite/grab samples (from July 2020 to April 2021) and passive samplers (from late January 2021 to April 2021).

Figure 2

Active COVID-19 cases (seven-day average) in Victoria, Australia (source: covid19data.com.au/Victoria), during the outbreak (a) and post-outbreak (b) and the corresponding monthly mean (horizontal bar within each box plot) SARS-CoV-2 (N gene and Orf1ab gene) copies were detected from wastewater samples collected using composite/grab samples (from July 2020 to April 2021) and passive samplers (from late January 2021 to April 2021).

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Genetic validation using amplicon sequencing and CRISPR DETECTR

Genetic validation confirmed 375 (94.7%) of the 396 RT-qPCR positive samples as true SARS-CoV-2 positive detections based on either the N or Orf1ab assay, including all but three of the dual-target positive samples (Table 2; Supplementary Table S1). Of these, 154 were confirmed by amplicon sequencing before CRISPR DETECTR testing was introduced in October 2020, five by amplicon sequencing post-October 2020, 214 by both sequencing and CRISPR DETECTR assay, and two by CRISPR DETECTR only, following failure to sequence. Of the 137 quantifiably positive samples for N and Orf1ab, 134 (97.8%) were confirmed, with 87, 26, and 21 confirmed by sequencing both amplicons or N or Orf1ab only, respectively. For single-target positive samples, all (100%) of 136 N assays and 74 (88%) of 84 Orf1ab assays were confirmed by genetic validation, respectively. Interestingly, amplicon sequencing and CRISPR DETECTR testing confirmed the presence of the SARS-CoV-2 amplicon in 29 of the 121 samples that exhibited late amplification in the N assay below the quantifiable level. This included 17 quantifiable samples confirmed as SARS-CoV-2 positive by Orf1ab and 12 that showed similarly late, unquantifiable amplification in the Orf1ab assay. We saw a similar result for 20 of the 139 samples that showed late, non-quantifiable amplification in the Orf1ab assay (Supplementary Table S1). These results were repeated in multiple sequencing replicates in separate sequencing runs. In each case, the negative RT-qPCR controls run with the samples were confirmed as SARS-CoV-2 negative, clearly demonstrating that the source of these sequence reads was not contamination. In a direct comparison, once the CRISPR DETECTR assay was introduced, all sequenceable samples were also confirmed by CRISPR DETECTR. In one instance, a sample was confirmed by CRISPR despite failing to sequence (Supplementary Table S1).

Table 2

Sensitivity results of RT-qPCR assay for N and Orf1ab genes

N onlyOrf1ab onlyBothn.q.Total
RT-qPCR positive 136 84 137 39 396 
Confirmed 136 (100%) 74 (88.1%) 134 (97.8%) 31 (79.4%) 375 (94.7%) 
 Sequencing only 51 18 67 137 
 CRISPR only 2 
 Sequencing and CRISPR 83 43 20 148 
 Sequencing negative and CRISPR  positive 2 
 Sequencing positive and CRISPR negative 0 
 Sequencing negative and CRISPR negative 13 (includes three CRISPR ambiguous)a 13 
 Confirmed by one amplicon 47 26 (includes one CRISPR ambiguous) 73 
Unconfirmed 0 (0%) 10 (11.9%) 3 (2.2%) 8 (20.6%) 21 (5.3)% 
 Sequencing only 
 Sequencing and CRISPR 9 (includes two CRISPR ambiguous) 2 (includes one CRISPR ambiguous) 8 (includes one CRISPR ambiguous) 19 
 CRISPR only 
N onlyOrf1ab onlyBothn.q.Total
RT-qPCR positive 136 84 137 39 396 
Confirmed 136 (100%) 74 (88.1%) 134 (97.8%) 31 (79.4%) 375 (94.7%) 
 Sequencing only 51 18 67 137 
 CRISPR only 2 
 Sequencing and CRISPR 83 43 20 148 
 Sequencing negative and CRISPR  positive 2 
 Sequencing positive and CRISPR negative 0 
 Sequencing negative and CRISPR negative 13 (includes three CRISPR ambiguous)a 13 
 Confirmed by one amplicon 47 26 (includes one CRISPR ambiguous) 73 
Unconfirmed 0 (0%) 10 (11.9%) 3 (2.2%) 8 (20.6%) 21 (5.3)% 
 Sequencing only 
 Sequencing and CRISPR 9 (includes two CRISPR ambiguous) 2 (includes one CRISPR ambiguous) 8 (includes one CRISPR ambiguous) 19 
 CRISPR only 

Note. Values in the bracket represent the percentage of RT-qPCR specificity. Symbol: n.q; non-quantifiable.

aDenotes samples that could not be confirmed as SARS-CoV-2 positive by sequencing or CRISPR analysis of Orf1ab, but were confirmed based on sequencing or CRISPR analysis of the N gene.The bold values only represent the total numbers in the RT-qPCR positively confirmed and unconfirmed results and the breakdown numbers within the confirmed and unconfirmed results are shown in non-bold letters.

Genetic validation could not confirm 21 (5.3%) of the 396 RT-qPCR-positive samples (Table 2). The resulting data did not include an identifiable target organism in each case, yielding only library adaptor or primer dimer sequences. We saw no instances in which amplicon sequencing identified a heterologous organism. However, we identified eight instances in which samples were positive by RT-qPCR for Orf1ab but produced a truncated sequence upon amplicon sequencing (marked as ‘Ambiguous’ in Supplementary Table S1). Assessment of these amplicon fragments on an Agilent TapeStation 4200 (Agilent Technologies, USA) was inconclusive as the resulting images contained many fragments across a broad range of sizes, and it was unclear if the expected full amplicon (119 bp) was present (representative examples in SupplementaryFigure S2B). Further independent assessment of these amplicon fragments by the Orf1ab CRISPR DETECTR assay using Orf1ab-guide RNA (CACATACCGCAGACGGTACAGAC) returned positive results for all amplicons (Supplementary Figure S3A). All amplicons were cleaned of probes/primers by 1 h incubation in ExoSAP-IT™ before CRISPR analysis, and we verified that these reagents were no longer detectable after clean-up based on NTC controls spiked with the same RT-qPCR mastermix. The sample was confirmed SARS-CoV-2 positive in three instances by amplicon sequencing following late, non-quantifiable N amplification. Interestingly, these fragment amplicons were reproducible upon repeat RT-qPCR testing and occurred during the early months of 2021.

This study describes implementing a highly sensitive SARS-CoV-2 detection methodology based on RT-qPCR coupled with amplicon sequencing or CRISPR DETECTR for confirmation within a fully operationalised adaptive wastewater monitoring programme in Victoria, Australia. During the study period, the programme was challenged by low rates of SARS-CoV-2 community prevalence and transmission. Therefore, it needed to achieve near single-molecule detection sensitivity from different sample types and to deliver readily verifiable true-positive results with precision and at scale and pace to inform important public health decisions.

Notwithstanding a small number (21) of unconfirmed test results, we identified no instances in which the RT-qPCR assay produced a confirmable false positive. Assuming that all unconfirmed results are false positives, this translates to an RT-qPCR detection specificity of ∼95% when including non-quantifiable amplification below the quantification threshold of the assay or ∼96.3% when excluding non-quantifiable amplification (Table 2). Importantly, post-PCR genetic validation readily identified these potential false positives. We identified eight cases where samples tested positive for Orf1ab via RT-qPCR but generated a truncated sequence upon amplicon sequencing. This truncated sequence was 100% consistent with the forward and reverse CCDC PCR primers and corresponding RT-qPCR FRET for Orf1ab (Kitajima et al. 2020) but lacked the rest of the amplicon sequence (Supplementary Figure S2A). Positive results from the Orf1ab CRISPR DETECTR assay using Orf1ab-guide RNA (CACATACCGCAGACGGTACAGAC) on these fragmented amplicons suggest they were not an artefact resulting from the amplicon sequencing process, which was run independently of the CRISPR assay. Moreover, the absence of detectable residual reagents confirmed that the observed results were not due to cross-reactivity with any leftover Orf1ab FRET probe. We cannot explain the source of this rare amplicon fragment despite discussing it at length with the RT-qPCR kit manufacturer (Perkin-Elmer pers. comm). We redesigned the Orf1ab DETECTR probe (Supplementary Figure S1B) to differentiate the truncated from full-length Orf1ab amplicon, assuming the former was a rare artefact possibly due to priming off degraded RNA templates. The redesigned Orf1ab-guide RNA (AAAACACAGTCTGTACCGTC) targeting the ‘missing’ regions of the Orf1ab fragment was then used to retest these ‘ambiguous’ amplicons, and they returned a negative result supporting this assumption (Supplementary Figures S1B and S3B). Unfortunately, we could not make a classical inference on detection sensitivity in a real-world application as we were unable to identify an alternative method with comparable sensitivity despite evaluating all major published RT-qPCR protocols [see Kitajima et al. (2020)] at the initiation of the study programme (data not shown). However, Black et al. (2021) estimated the LOD for the Victorian programme to be one viral genome copy per mL of raw wastewater by spiking wastewater samples used in the present study with gamma-irradiated SARS-CoV-2 viruses before purification and RNA extraction. The authors reported that this limit was primarily influenced by viral recovery (estimated at ∼38%) rather than PCR sensitivity. Furthermore, Schang et al. (2021) showed that the LOQ for the passive sampling methods employed in this programme was 1.8 viral genome copies per mL of raw wastewater.

Victoria's SARS-CoV-2 wastewater monitoring programme was designed specifically to detect SARS-CoV-2 by N- or Orf1ab-targeted RT-qPCR, with confirmation by amplicon sequencing or CRISPR DETECTR assay. Therefore, we did not consider its diagnostic sensitivity or specificity in identifying active community cases within a catchment or its ability to differentiate these from other possible sources, including prolonged faecal shedding or movement of individuals among catchments. However, Black et al. (2021) found that most of the detections obtained by the programme corresponded to at least one known active case in the catchment at the time of sampling, and, overall, the programme had a diagnostic specificity for active community cases, as defined by their place of residence, ranging from 87 to 95%, depending on the distance from the sampling site and recency of infection.

During the study period, SARS-CoV-2 cases in Victoria, Australia, were low compared to many other national and international jurisdictions (Kennedy et al. 2021), thanks largely to public health measures, such as testing, contact tracing, and mandatory mask-wearing (Trauer et al. 2021). Additionally, the SARS-CoV-2 wastewater surveillance programme in Victoria also played a crucial role in early detection, which has informed policy decisions and monitoring efforts, particularly since its inception following the second wave (Patten et al. 2020).

Our approach had the requisite sensitivity and specificity for routine use, including periods of very low or no SARS-CoV-2 infections or transmission. The multi-tiered decision matrix developed allows for a logical interpretation of results, effectively addressing public health challenges and timely intervention. The extension-PCR-based amplicon sequencing and CRISPR DETECTR assay methods were found to be robust, reliable, and of significant value in assessing the diagnostic sensitivity of RT-qPCR. This verification step was refined over time and was critical in ensuring the results could be used confidently in a rapid public health response. In this last regard, the CRISPR DETECTR assay was particularly effective, enabling rapid genetic confirmation of PCR results at low cost and within a few hours (Kaminski et al. 2021) instead of the ∼48 h turnaround time required by amplicon sequencing. By employing a dual-target RT-qPCR approach, we can enhance specificity and reduce the likelihood of ambiguous results, which is important to monitor for pathogens, particularly when community cases are low. By integrating these methodologies, our approach establishes a comprehensive strategy that can be adapted to any wastewater surveillance for novel, emerging, or re-emerging infections [e.g., MPox (Otu et al. 2022) and polioviruses (Asghar et al. 2014)] or high-priority influenza variants (Vo et al. 2023) in public health responses during periods of low to no known community transmission.

This study was funded by the Victorian Department of Health and Water Research Australia (Project 2064). AR Jex acknowledges additional funding through the Australian National Health and Medical Research Council Investigator Grant program (APP1194330). WEHI acknowledges funding through the Victorian State Government Operational Infrastructure Support and the Australian Government National Health and Medical Research Council Independent Research Institute Infrastructure Support Scheme.

The authors declare there is no conflict.

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