Next Article in Journal
Impact of Environmental Pollutants on Otorhinolaryngological Emergencies in the COVID-19 Era
Next Article in Special Issue
Screening Urban Soil Contamination in Rome: Insights from XRF and Multivariate Analysis
Previous Article in Journal
Worker Safety in High-Field NMR Spectroscopy Laboratories: Challenges and Risk Assessment
Previous Article in Special Issue
Integrating Nature-Based Solutions into Circular Economy Practices: A Case Study on Achieving Net-Zero Emissions at the Asian Institute of Technology
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Environments
Volume 12
Issue 4
10.3390/environments12040114
environments-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Australian and New Zealand Laboratory Experience and Proposed Future Direction of Wastewater Pathogen Genomic Surveillance

by
Avram Levy
1,*,
Christina Crachi
2,
Jake Gazeley
1,
Joanne Chapman
3,
Anna Brischetto
4,
David Speers
1,
Joanne Hewitt
3,
Amy V. Jennison
4 and
The Wastewater Surveillance Working Group, Communicable Diseases Genomics Network of Australia
1
PathWest Laboratory Medicine WA, Nedlands, WA 6009, Australia
2
Microbiological Diagnostic Unit Public Health Laboratory, University of Melbourne, Parkville, VIC 3010, Australia
3
Institute of Environmental Science and Research Ltd., Porirua 5022, New Zealand
4
Public and Environmental Health Reference Laboratories, Pathology Queensland, Queensland Health, Brisbane, QLD 4006, Australia
*
Author to whom correspondence should be addressed.
Environments 2025, 12(4), 114; https://doi.org/10.3390/environments12040114
Submission received: 7 February 2025 / Revised: 27 March 2025 / Accepted: 2 April 2025 / Published: 8 April 2025
(This article belongs to the Special Issue Environments: 10 Years of Science Together)
Versions Notes

Abstract

:
Wastewater pathogen surveillance was rapidly implemented across Australia and New Zealand as a public health tool during the COVID-19 pandemic. To assess method consistency and identify opportunities for harmonization, we surveyed all Australian and New Zealand Laboratories conducting government-funded wastewater pathogen surveillance. The survey demonstrated alignment of some method choices, particularly municipal wastewater treatment plant (WWTP) sampling and the use of electromagnetic membrane filtration followed by RT-qPCR. However, key differences were observed in the wastewater sample volumes; nucleic acid purification methods; validation approaches; and sequencing, analysis, and reporting methods for SARS-CoV-2 lineages. A lack of consensus on best-practice methods was evident, highlighting the need for interlaboratory sample and data exchanges to support validation and comparability. Following the pandemic period, several jurisdictional programs were discontinued despite the mounting international evidence for the utility of wastewater-based epidemiology for a range of pathogens. Subsequently, a nationally funded program was announced in Australia, necessitating the re-establishment of laboratory capacity for some jurisdictions and expansion of target pathogens for other centers. The results of this survey are intended to inform the re-establishment and enhancement of regional capacity and to provide a foundation for best-practice knowledge sharing and approach harmonization.

1. Introduction

Wastewater surveillance is an effective tool in public health, enabling monitoring and tracking of pathogens in communities [1,2,3,4,5]. This approach provides a non-invasive and potentially cost-effective way to gather real-time data on population health [6,7,8,9]. Poliovirus surveillance using wastewater has been in operation for many decades, primarily relying on cell culture methods [10]. During the COVID-19 pandemic, laboratories around the world rapidly implemented molecular testing for SARS-CoV-2 from wastewater [6,7,11,12,13,14]. In Australasia, this was facilitated by the Collaboration on Sewage Surveillance of SARS-CoV-2 (ColoSSoS) program, a community of practice established by Water Research Australia [15]. For a period, SARS-CoV-2 wastewater surveillance was occurring in all Australian States and two Territories as well as in New Zealand, collectively described as jurisdictions here. During times of low community transmission, the qualitative detection of SARS-CoV-2 in wastewater preceded clinical cases, acting as an early warning system that could help guide public health interventions [16,17,18,19]. Due to the elimination strategies followed by the Australian and New Zealand governments, researchers in these countries were able to assess the sensitivity of wastewater surveillance for SARS-CoV-2, since case numbers (such as returned travelers in managed quarantine) were precisely known [16,20,21]. This contrasted with most places in the world where COVID-19 was widespread in the population by the time wastewater surveillance for the virus was established. Subsequently, with increasing community transmission, the quantification of SARS-CoV-2 using reverse transcription (RT)-qPCR in wastewater allowed for unbiased surrogate monitoring of case numbers as the proportion of clinical cases being tested decreased [14,22,23].
More recently, sequencing of SARS-CoV-2 in wastewater has been increasingly adopted globally [24,25,26], including in Australia [20,23,27] and New Zealand [28]. This has allowed for the identity and relative proportion of SARS-CoV-2 lineages circulating in communities to be monitored, as well as the early identification of variants of concern [23,26,29,30,31,32,33]. Following this international capacity development, there has been increasing interest in maintaining and enhancing wastewater-based surveillance (WBS) systems in Europe [34,35] and North America [36,37]. However, in Australasia, the number of jurisdictions with funded programs and the overall number of samples tested has diminished, especially since May 2023, when the WHO declared an end to COVID-19 as a public health emergency [38,39]. Jurisdictions who successfully expanded into genomics and provided lineage trend data to their Health Departments and the public were generally able to maintain their programs.
With the establishment of the Global Consortium for Wastewater and Environmental Surveillance for Public Health (GLOWACON) by the European Commission Joint Research Centre in March 2024 [34] and the ongoing National Wastewater Surveillance System (NWSS) run by the CDC in the US [37], a continuation and expansion of wastewater surveillance globally is anticipated. It is therefore important to identify best-practice approaches to assist Australasian public health laboratories in (re-)implementing, sustaining, and accrediting wastewater surveillance methods. Following this, it is likely there will be efforts to explore whether method harmonization (at least on a regional scale) will be feasible and/or desirable [40]. In this paper, we examine the development of wastewater surveillance laboratory systems, primarily for SARS-CoV-2, in Australian jurisdictions and in New Zealand. This will provide a case study for the roll-out of such programs at pace during the early stages of a pandemic and is intended to inform the re-establishment and enhancement of capacity.
The Communicable Diseases Genomics Network (CDGN) Wastewater Surveillance Working Group was established in March 2023 to discuss and harmonize approaches for wastewater pathogen genomic surveillance across Australia and New Zealand and to support the development of best-practice methodologies. A scoping survey was developed to capture current and past wastewater COVID-19 surveillance practices and distributed to all laboratories undertaking government-funded wastewater surveillance for SARS-CoV-2 in nine jurisdictions (i.e., the six states and two territories of Australia, plus New Zealand) in November 2023. This survey (Appendix A) captured the methods used by each jurisdiction from sample collection to reporting. At the time the survey was distributed, most jurisdictions had been running a wastewater surveillance program for the detection of SARS-CoV-2 RNA for at least 3 years, with each program developed independently by each jurisdiction. The survey was developed to gain an understanding of the current degree of similarity in approaches and assess whether there was scope to work towards more harmonized approaches in the future. Here, we amalgamate and summarize the findings from this survey with the aim to inform best practices and future application of wastewater surveillance across Australia, New Zealand, and beyond.

2. Materials and Methods

The survey was designed and collated by members of the CDGN Wastewater Surveillance Working Group using the platform Qualtrics. Sections of the survey were divided into sample collection (20 questions), viral concentration methods (3 questions), extraction (6 questions), sequencing (8 questions), and result reporting (4 questions), where it was not mandatory to fill in each segment. The full survey questions are included in Appendix A.
The survey was distributed via email from the CDGN on the 20th of October 2023 to those who were identified as stakeholders for all state-wide (Australia) and nation-wide (New Zealand) SARS-CoV-2 in wastewater surveillance programs in Australasia. Survey responses closed on the 15th of November 2023, after which responses were collated and examined for completeness. Some jurisdictions were asked to provide additional information, resulting in the survey being extended until the 14th of February 2024. Upon receiving additional responses, the data received were collated and analyzed by the CDGN Wastewater Surveillance Working Group.

3. Analysis and Discussion

Eight of the nine jurisdictions approached across Australia and New Zealand responded. Table 1 summarizes the key processes or characteristics of the systems reported.

3.1. Sampling

Four out of eight jurisdictions reported that wastewater samples were collected by a single water utility. Two jurisdictions indicated that multiple water utilities were responsible for sample collection. One jurisdiction reported that a laboratory service provider collected the samples, and one jurisdiction did not provide a response. Noting that certain jurisdictions used multiple methods, five out of eight jurisdictions collected autosampler composite samples. Of these, three jurisdictions used a representative sampling length of 24 h, one for ≥48 h, and one did not provide a sampling length. Three out of eight jurisdictions collected passive sampler composite samples. Of these, one jurisdiction deployed passive samplers for seven days, one for two to four days, and one did not provide the sampling length.
The number of unique locations from which samples were collected in each jurisdiction ranged between 3 and 45. Most jurisdictions (5 out of 8) collected samples from fewer than 10 unique locations per sampling period. Five jurisdictions collected 100% of their samples from wastewater treatment plants (WWTPs), two jurisdictions collected from airports, and one jurisdiction collected samples from sewers (N = 7) and an individual facility/building. Five of the seven jurisdictions that collected samples from municipal WWTPs provided details on the frequency of sample collection. This ranged from two times per month (approximately fortnightly) to eight times per month (approximately twice per week). For the two jurisdictions that reported collecting wastewater from airports, sampling frequency ranged from once per week to three times per week. The jurisdiction collecting samples from sewers and facilities/buildings indicated that sampling occurred weekly. One jurisdiction indicated that metropolitan samples were collected twice per week and once per week for regional locations.
Five of the seven jurisdictions that collected samples from WWTPs provided details on the respective population catchment sizes, ranging from less than 50,000 to about 2,000,000. The jurisdiction that collected samples from sewers indicated population catchment sizes ranging from approximately 50,000 to 100,000, while the individual facility/building had a catchment size of less than 50,000.

3.2. Viral Concentration Methods

Seven of the eight jurisdictions provided answers to survey questions on virus concentration methods. Two of the seven jurisdictions stated they performed pre-acidification prior to the viral concentration step. Both these sites used electromagnetic membrane filtration. Two of the seven jurisdictions stated they performed pre-treatment with MgCl2, with both these jurisdictions also using electromagnetic membrane filtration. One of the seven jurisdictions stated “No” as their response to the use of pre-treatments but later clarified that MgCl2 was used as part of the viral concentration method using electromagnetic membrane filtration. One of the seven jurisdictions (that used polyethylene glycol (PEG) precipitation as their viral concentration method) left this answer blank, and one of the seven jurisdictions entered an answer that was assumed to be answering a different question in the same section.
Six of the seven responding jurisdictions concentrated wastewater by electromagnetic membrane filtration, while the other used PEG precipitation. Two of the seven jurisdictions processed volumes of 250 mL, one of which was the jurisdiction using PEG concentration. Of the remaining five jurisdictions, all of which used electromagnetic filtration, three concentrated 50 mL, one concentrated 100 mL, and one reported using 50–100 mL A review of methods used for virus concentration internationally during the early stages of the pandemic [41] found that prefiltration-salt addition electronegative membrane filtration of ≤50 mL and prefiltration PEG-based separation of 50–1000 mL were both highly recommended as methods that maximized virus recovery, suggesting that Australasian laboratories were largely following best-practice methods [41,42].

3.3. Extraction

Seven of the eight jurisdictions provided information about their nucleic acid extraction methods. In all but one, nucleic acid extraction was undertaken in the same laboratory as the virus concentration. Two jurisdictions reported using more than one extraction method, with one reporting a switch of platform (Kingfisher Apex to the Kingfisher Flex (ThermoFisher, Waltham, MA USA)) system without reporting the specific extraction kit(s) used, and another reporting the use of both the MagMax Microbiome Ultra Kit (ThermoFisher) and the RNeasy Power Microbiome Kit (Qiagen, Venlo, The Netherlands). The remaining jurisdictions reported using a single extraction kit and/or platform, but there was little consistency in choice or the manufacturer.
The following kits were reported, each by a single jurisdiction: Environ Water RNA Kit (Zymo; Irvine, CA, USA); RNeasy PowerWater Kit (Qiagen; Venlo, The Netherlands); High Pure Viral Nucleic Acid Kit (Roche; Basel/Kaiseraugst, Switzerland); MagMAX Microbiome Ultra Nucleic Acid Kit (Applied Biosystems; Waltham, MA, USA) in combination with the MagMAX Express 96 magnetic particle processor (Applied Biosystems); and the Kingfisher system (ThermoFisher), though the specific extraction kit used was not specified. Taken together, these responses reveal that three jurisdictions used magnetic bead-based technology (MagMax kit for RNA extraction with processing by Kingfisher or MagMax Express instruments), while three used silica spin column-based methods (kits manufactured by Zymo, Roche, and Qiagen) and one jurisdiction reported using both approaches.
The MagMax Microbiome Ultra kit reported to be used by two jurisdictions (and presumably by a further two jurisdictions that reported using the KingFisher system without specifying which extraction kit) targets both RNA and DNA, as does the silica column-based Roche kit. In contrast, the other two silica spin column-based methods specifically target RNA, although it is likely that DNA is co-extracted to some extent unless a DNA digestion step such as DNase I treatment is completed during extraction.
The recovery of SARS-CoV-2 RNA from wastewater concentrates may vary greatly depending on the methods and kits chosen. However, little information was available at the start of the pandemic about the relative recovery efficiency of different commercial nucleic acid extraction kits, or indeed between magnetic-bead and silica-column based approaches for wastewater epidemiology applications [42], where inhibitors and/or debris may be present. The availability of a set of viral concentrate standards would allow inter-laboratory comparisons to be undertaken in future.
Jurisdictions were also asked whether they used an RNase inhibitor, and if so, at what stage. Responses were again mixed, with three jurisdictions reporting that they did not use an RNase inhibitor, one reporting use during sample preparation, one during extraction, one during the reverse transcription (RT) step, and one added an RNase inhibitor after extraction to stabilize the RNA during transport to another laboratory for qPCR amplification.

3.4. Quantitative Detection

Jurisdictions were asked to provide information on their methods for the quantitative detection of SARS-CoV-2 RNA in wastewater. Of the seven respondents, five answered yes to using quantitative detection of SARS-CoV-2 RNA, with all noting that they use RT-qPCR. Commercial kits were used by all but one laboratory, and all PCR assays for SARS-CoV-2 targeted the nucleocapsid (N) gene. Three laboratories used the same commercial kit (PerkinElmer SARS-CoV-2 Real-time RT-PCR Assay), which is a duplex assay that also detects ORF1ab.
Only five laboratories responded to questions relating to controls and validation of the workflow components (Table 2). The use of PCR controls was common; however, the inclusion of controls at other stages of the work was more variable (Table 2). Some jurisdictions used different laboratories for PCR and sequencing, and therefore, information on certain steps may not have been available to survey respondents. The validation of PCR was reported to have been performed by three laboratories (with another jurisdiction reporting that the validation of concentration, sequencing, and bioinformatics was in progress). Among the three laboratories specifying validation steps, the level of detail reported and approaches used varied. Validation of concentration, PCR, sequencing, and bioinformatics was reported by all three laboratories. One laboratory specified that validation of all these steps was performed by spike-in experiments (where surrogate viruses are added to the wastewater before concentration to assess the concentration and extraction efficiency) and comparative analyses. For the other two laboratories, viral concentration was validated using inactivated SARS-CoV-2 and interlaboratory panels by one laboratory, while the other reported using recovery percentages. RT-qPCR was validated using sequencing to validate PCR-positive samples for one laboratory, with the other laboratory determining specificity, sensitivity, limit of detection, and limit of quantitation. The methods used to validate sequencing results are described in the sequencing section below.
The lack of responses on method validation for many laboratories is concerning. It may reflect the fact that wastewater surveillance programs were stood-up at pace during the early stages of the COVID-19 pandemic, at a time when spike-in controls, standards, and reference material were lacking, especially for laboratories based in the Southern Hemisphere, or may reflect the fact that some survey respondents were not familiar with which validation methods had been used at certain steps. Nevertheless, validation steps, such as calculation of viral recovery efficiency and limits of detection, are crucial to ensure that results are reliable and interpretable [43,44]. As such, inter-laboratory validation using a widely available set of standards and controls is highly recommended as surveillance programs are maintained or re-established globally. International collaborative efforts such as the GLOWACON platform could play a key role in this area.
One laboratory reported the transport of RNA prior to RT-PCR over a 0–2-day period, and two laboratories reported the transport of cDNA prior to sequencing, which could take greater than 5 days. Storage time and temperature have been shown to have minimal impacts on SARS-CoV-2 N-gene quantification or variant sequencing [45]; however, within- and between-laboratory validation of this for the specific storage and transport methods chosen would confirm whether transporting the material results in a loss of signal.
In summary, RT-PCR targeting the nucleocapsid gene was the consensus detection and quantitation method. The survey did not cover the quantification standards or how these were calibrated. Variable degrees of validation and transport time were reported.

3.5. Sequencing

All seven of the jurisdictions undertaking municipal WWTP wastewater sampling completed the survey questions regarding sequencing of SARS-CoV-2 variants, with six jurisdictions reporting regular sequencing of their samples (Table 3).
Whole genome sequencing (WGS) using tiled amplicons was used by four of the six jurisdictions undertaking a variant analysis, one of which reported using a blend of WGS and spike gene (receptor binding motif) amplicon sequencing. Two jurisdictions reported using spike gene amplicon sequencing. Illumina sequencing was the only technology specified, with iSeq, MiniSeq, MiSeq, and NextSeq550 instruments used (Illumina, Inc., San Diego, CA, USA), likely informed by the availability of equipment and/or expertise rather than ideological preference.
The sequencing controls used by jurisdictions included negative sequencing control (five jurisdictions) and positive sequencing control (one jurisdiction). One jurisdiction did not respond to the question regarding sequencing controls. Bioinformatic quality control criteria, below which a result would not be reported, varied amongst jurisdictions. Thresholds for laboratories using WGS included a minimum genomic coverage of >60% to >90% and minimum average quality scores, while the laboratories using spike gene amplicon sequencing required a minimum number of reads, read abundance, and read lengths. All four laboratories reporting their deconvolution tool used Freyja, which allows for an estimation of the relative abundance of SARS-CoV-2 lineages in a mixed sample such as wastewater [25] and has recently been shown to outperform other deconvolution tools [46].
Three jurisdictions reported undertaking sequence validation, one jurisdiction stated validation was in progress, and two jurisdictions did not indicate whether any sequencing validation had been undertaken. Bioinformatics processes were validated in four jurisdictions. The survey did not capture details of how the validation of variant sequencing results was undertaken. In future, inter-laboratory validation using a common set of samples of a known variant composition is recommended, especially as Australia transitions to a nationally coordinated wastewater surveillance program with public reporting of national results (see below).

3.6. Reporting

The last section of the survey focused on how jurisdictions reported wastewater sequencing results, with six of the eight jurisdictions providing at least some information. Five jurisdictions indicated that they reported the relative abundance of lineages (Pango lineage designation), and three of these jurisdictions provided direct comparisons between wastewater and clinical sequencing results. However, the threshold required for a lineage to be reported varied. One jurisdiction only reported lineages measured at 10% or more relative abundance, two applied a 5% threshold, and one used a 1% threshold, while others did not specify their reporting cut-off or whether a threshold was applied.
There was also variability in how lineages were designated in reports. Four of the six jurisdictions reported lineages at the parental level (i.e., grouping individual child lineages under a common parental ancestor), unless a sub-lineage was classified as a variant of interest (VOI) or variant under monitoring (VUM) [47], in which the VOI/VUM sub-lineage was specifically separated and reported at a new parental level (e.g., BA.2.X further separated to BA.2.75.X). In contrast, two jurisdictions reported the most derived sub-lineage designations produced by their bioinformatic pipeline. All six jurisdictions indicated that sequencing results were reported to the relevant public health authority for that jurisdiction, and two jurisdictions stated that the data were also publicly available via an external dashboard.
These findings highlight the lack of standardization in lineage reporting thresholds across jurisdictions, reflecting broader global challenges in wastewater-based genomic surveillance. The choice of minimum relative abundance thresholds can significantly impact data interpretation, influencing whether low-frequency lineages are reported or excluded. Studies have demonstrated that increasing the reporting threshold reduces false positives but raises the risk of missing emerging lineages, with sequencing depth and genome coverage also affecting detection accuracy [48]. Studies have successfully identified mutations at <5% relative abundance, detecting them in wastewater before clinical case identification [49], suggesting that a 5% cut-off may be too high.
Differences in lineage aggregation strategies further complicate comparisons across jurisdictions. Reporting at the parental level simplifies analysis but may obscure epidemiologically relevant sub-lineages, particularly those not classified as VOIs or VUMs. Reporting highly derived sub-lineages may improve resolution but will increase data complexity. Comparisons of highly derived sub-lineages between wastewater and clinical cases have shown a reduction in correlation compared to parental designations in Western Australia [23]. Some studies have recommended aggregating related lineages under their parent designation until they reach a pre-defined abundance to balance granularity and usability [50].
Standardized guidelines for reporting thresholds and lineage aggregation in wastewater sequencing could improve comparability between Australian and New Zealand jurisdictions with potential to enhance public health utility. However, further work is needed to refine this practice.

3.7. Current Challenges, Limitations, and Strengths of Wastewater Surveillance

Funding remains a critical limitation for wastewater surveillance programs in Australia and New Zealand. Rapid capacity development during the COVID-19 pandemic enabled the establishment of these programs, but as pandemic-related measures were scaled back, some jurisdictions reduced or discontinued their programs. Others recognized the ongoing value of wastewater-based epidemiology and expanded their programs to track additional pathogens, leveraging existing laboratory capacity and increasing efficiency by using the same samples for multiple pathogens. Maintaining laboratory capacity to rapidly detect emerging threats remains critical, particularly for pathogens such as mpox virus, avian influenza, and flaviviruses [51,52,53]. However, one of the main challenges to continued investment is that real-world applications of wastewater surveillance to public health decision-making remain limited, with poliovirus surveillance being the most established example [10]. This is changing, with an increasing number of studies showing the utility of wastewater surveillance to directly inform public health actions [54,55,56], along with the development of frameworks to integrate wastewater data into existing public health surveillance systems [57,58]. Documenting this evidence base remains essential to support its adoption in public health policy and prevention strategies. Cost–benefit analyses would provide valuable insights into whether maintaining wastewater surveillance beyond emergency periods is a justifiable long-term investment. Examples of such analyses are starting to emerge [59,60].
The United States’ National Wastewater Surveillance System (NWSS) offers a notable example of how sustained funding and integration into national surveillance frameworks can support the long-term viability of wastewater monitoring. Established and managed by the Centers for Disease Control and Prevention (CDC), NWSS has, through the Epidemiology and Laboratory Capacity Cooperative Agreement, embedded wastewater surveillance into public health infrastructure. By 2022, NWSS supported wastewater surveillance across 42 US states and multiple territories, providing continued pathogen monitoring beyond a pandemic response [36,37]. The incorporation of commercial contracts and academic collaborations further demonstrates how diversified funding streams can support program expansion, ensuring data quality and effective integration into public health decision-making.
In the absence of recurrent, sustainable public health funding, Australia and New Zealand could benefit from examining the NWSS model to maintain and expand their wastewater surveillance capabilities. While both countries established extensive monitoring systems during the COVID-19 pandemic, many programs have been reduced or discontinued as emergency funding ceased. Integrating wastewater surveillance into existing public health reporting structures, fostering multi-sectoral collaborations, and diversifying funding sources, like the NWSS approach, could improve program sustainability.
Beyond traditional public health funding, diversifying financial support is key to ensuring the survival, cost-effectiveness, and capacity enhancement of wastewater surveillance programs. This presents challenges for public health laboratories and units in Australia and New Zealand, which may lack experience in securing external funding or have limited publication and grant success records. Expanding cross-sector collaboration, including partnerships with industry, and broadening the application of wastewater surveillance to other environmental samples and multi-pathogen panels could further enrich value and sustainability.
For example, there is increasing interest in using wastewater to monitor for antimicrobial resistance [35,61,62]; however, this presents considerable new challenges in methods, test design, and interpretation. It is important to recognize that SARS-CoV-2 shedding in wastewater occurs at much greater concentrations than that for most respiratory pathogens, due to the virus binding to ACE2 receptors in the ileum and colon [63,64]. Pathogens occurring at lower concentrations in wastewater may require more refined concentration methods or may never be amenable to wastewater surveillance. The concentration methods used by jurisdictions in this survey can have variable yields and may not be ideal for all virus particles, with surface charge and other virion properties dictating method suitability and leaving considerable opportunity for method advances. Popular concentration methods almost universally focus on targeting the properties of virus particles and may be unsuited to bacterial or eukaryotic pathogens, or to free nucleic acid. PCR-inhibitor removal methods could also be further improved, with many methods targeting the supernatant despite the considerable pathogen abundance in wastewater solids. A pathogen agnostic high-yield concentration method, if developed, would profoundly enhance the potential applications of wastewater pathogen surveillance.
Detection method technologies applicable to wastewater are relatively well developed but often cost-prohibitive. Real-time quantitative PCR remains the method of choice in Australasia for ease of use, turnaround time, sensitivity, scalability to increased throughput, and cost effectiveness. However, this method presents validation and confirmation challenges has limited multiplexing opportunity in the absence of array panels, and sensitivity may be impacted by various factors including the volume of nucleic acid tested, the presence of PCR inhibitors, and the choice of reagents and equipment. Digital PCR offers improved quantification, sensitivity, and accuracy and is less affected by PCR inhibitors compared to qPCR, making it particularly useful for low-concentration targets in wastewater [65,66,67]. However, its higher costs and lower throughput may limit routine application in surveillance programs. Hybrid capture panels and unbiased metagenomics are becoming cheaper but come with set-up costs, and deep sequencing may be required to achieve the desired sensitivity for wastewater samples. Finally, there are inherent limitations to the sample itself, including the sampling source; the type (grab/passive/auto-sampler); the time period over which a sample is collected; variable levels of dilution; and the extent to which viral persistence in wastewater is affected by temperature (in the sewer and during transport), chemical interferences, storage time, and processing decay [68]. Together, these limitations are considerable and present long-term scientific challenges.
The strengths of wastewater surveillance can be summarized into two key concepts, namely objectivity and cost-effectiveness. Unlike case-based surveillance systems, wastewater surveillance is not biased by health-seeking and testing behaviors and thus is not affected by increases in point-of-care or self-testing or by reduced clinical testing due to cost pressures. Wastewater captures asymptomatic, mildly symptomatic, and pre-symptomatic infections. Pathogen detection can be extremely sensitive (e.g., SARS-CoV-2, poliovirus) [21], providing effective community surveillance for new and emerging pathogens and drug resistance. When compared to case-based surveillance, wastewater is cost effective as relatively few samples are needed to cover large populations and provide data on pathogen detection, disease prevalence, and disease dynamics over time. With an accelerating rate of emerging pathogens due to human–animal interactions and climate change, wastewater surveillance is ideally placed to complement and alleviate the reliance on costly case-based surveillance systems.
In this survey, less than half of responding laboratories indicated some form of assay validation had been performed. The same number of laboratories indicated that clinical case data were compared with wastewater results, an important mechanism to provide a sense of validation for the public health use of wastewater data. It is not clear from this survey whether laboratories that did not respond to the question about method validation did not undertake validation activities or just did not have the information needed to respond to the question. It is not known if any decisions to not pursue validation were a result of uncertainties around how to achieve the validation, time pressures to implement programs, absence of quality assurance testing programs, other factors, or a combination of factors. The example of one laboratory leveraging off the validation of another demonstrates that laboratories will consider reducing the burden of validation exercises by aligning their practices. Recognizing this as a need and establishing the communication and support structures to facilitate method and knowledge sharing, along with guidelines for assay validation, will provide much needed support for laboratories gearing up to test wastewater for public health. Wastewater epidemiology communities of practice are increasing globally, including the aforementioned GLOWACON and NWSS platforms, as well as the NSF Research Coordination Network for Wastewater Surveillance [69], the ODIN Environmental and Wastewater Surveillance Community of Practice [70], Water Research Australia Wastewater-Based Epidemiology Community of Practice meetings [71], and the Communicable Diseases Genomics Network of Australia’s Wastewater Working Group [72].

3.8. Future Recommendations and Considerations for Wastewater Surveillance

The laboratory capacity developed across Australasia for SARS-CoV-2 wastewater surveillance, the engagement with and support from water utility providers, and the public health policies and action use cases implemented were the result of considerable investment. It is important that the lapse in identifying ongoing funding sources for these systems is short, so that capacity, knowledge, and public support are not lost.
Whilst finalizing this report, the Australian Government (Interim Australian Centre for Disease Control) announced a commitment to “establish a comprehensive national surveillance system that incorporates wastewater surveillance to facilitate disease detection, monitoring, risk assessment, and national data-sharing” [73]. This program will include sentinel surveillance across 50 sites for selected national priority pathogens, including SARS-CoV-2, influenza A virus (including H5), influenza B virus, respiratory syncytial virus, poliovirus, and the ability to add priority pathogens in response to emerging threats. The CDGN Wastewater Working Group welcomes this announcement and is hopeful for a similar commitment from New Zealand, where science sector reforms are currently underway [74]. Ongoing funding, national coordination, and the identification of key deliverables for the Australian program will ensure the capacity built previously is not lost but leveraged upon for expansion to other pathogens and continued development.
Wastewater pathogen detection and characterization has multi-sector relevance across environmental, animal, and human health and therefore falls under the umbrella of One Health [75,76,77]. Achieving connectivity and effective communication across the stakeholder sectors will ensure optimal method implementation, cost-effectiveness, and cross-sector policy consideration. This remains a sizeable challenge, with communication and knowledge sharing gaps, but there are facilitative knowledge sharing frameworks in place such as the Water Research Australia Wastewater-Based Epidemiology Community of Practice meetings, GLOWACON, and others mentioned previously which offer multi-sector representation. Challenges will occur in communicating the results of cross-sector relevance without agreed-upon methods and result formats, as well as defined interpretation and reporting pathways. Result verification by specialized laboratories will remain critical, particularly when metagenomics is in use, yet sample, extract, and sequence sharing requires pre-agreed governance arrangements, many of which are not in place. Increasing the audience breadth when reporting is an important early step in increasing result visibility and promoting multi-sector engagement and can be achieved by promoting the use of public dashboards. The authors (JC and JH) note that public feedback on the New Zealand wastewater dashboard (www.poops.nz; accessed on 21 March 2025) has been overwhelmingly positive, with the main criticism being that additional sites should be included. This shows that the public value having access to population-level disease surveillance data upon which they can make informed decisions regarding risks [78,79].
For laboratories implementing wastewater surveillance protocols, there is a need for sample and data exchanges to inform decisions on best practice, both in the wet and dry laboratory settings [80]. This is particularly relevant given the diversity of methods in use, as identified by these survey results, as well as the challenges in working with these complex samples. As new technologies and approaches emerge, understanding performance metrics is necessary to inform laboratory choices. Consensus on method performance leads to the standardization of approaches across laboratories, facilitating a comparison of results between jurisdictions and coordinated national, and even international reporting. Standardization would also be enhanced through a common funding model with a prescribed minimum set of target pathogens. A comparison with other surveillance data is critical to demonstrate system effectiveness, and early results must be shared effectively to guide implementation and enhance capacity. Networks such as the CDGN Wastewater Working Group and the Water Research Australia Wastewater-Based Epidemiology Community of Practice can perform functions such as (1) providing an avenue to discuss challenges and solutions, including collating laboratory optimization and comparison data as a resource for others to use; (2) facilitating a broader forum for knowledge sharing including public health use cases of wastewater surveillance data; (3) offering guidance on best-practice methods and validation options, including bioinformatic and public health validation by comparison to other surveillance data sources; (4) facilitating inter-laboratory sample and data exchanges, targeted to the current needs of laboratories and public health units; and (5) enhancing connections with international groups developing enhanced wastewater surveillance methods, providing a forum and communication pathway for addressing some of the inter-sector challenges described above.

4. Conclusions

The responses to our survey of SARS-CoV-2 wastewater surveillance practices highlighted the challenges associated with rapidly implementing a regional SARS-CoV-2 wastewater surveillance program. The identified challenges included choice of method for sample concentration, extraction and amplification, high-throughput sequencing of complex samples, and the associated bioinformatic intricacies, as well as proving the public health use cases and meeting reporting expectations in a timely and robust manner. Areas of key similarity in systems and processes were evident, whereas a lack of consensus in other areas was also obvious. Similarities included a focus on municipal WWTP sampling, generally at fewer than ten locations per jurisdiction predominantly using autosampler devices and a preference towards electromagnetic membrane filtration. The quantitative detection of SARS-CoV-2 was universally by RT-qPCR targeting the nucleocapsid gene, followed by whole genome tiled or spike-gene amplicon sequencing using Illumina platforms. Reporting of lineage abundances was common, preferably alongside clinical data. Differing approaches were evident in sampling (Table 1), the use of pre-treatments, volumes concentrated, RNA purification kit choice, PCR assay validation approach, quality controls incorporated, and public reporting. The impact these similarities and differences had on consistency across laboratories is not yet clear.
The results of this survey have shown that there is currently no standardized or widely accepted complete workflow for wastewater COVID-19 surveillance in Australia and New Zealand, which is typical of emerging capacity and is productive for innovation and best-practice method selection. While we do not necessarily advocate for a single workflow across all laboratories in Australasia, it is important to review the approaches implemented and support laboratory decision making with sample exchanges and other opportunities for workflow evaluation. This is especially important once laboratories are providing results to a national surveillance and reporting program. This paper highlights the complexities associated with wastewater surveillance and the importance of communication, method sharing, and innovation. Whilst written at a time of low funding within New Zealand and Australia, the authors believe there is undisputed value to wastewater as a public health surveillance tool and laboratories should be prepared and supported to reinstate and expand programs.

Author Contributions

Conceptualization, A.L., C.C., J.G., J.C., A.B., J.H. and A.V.J.; methodology, A.L., C.C., J.G., J.C., A.B., J.H. and A.V.J.; software, C.C.; formal analysis, A.L., C.C., J.G., J.C., A.B., J.H. and A.V.J.; investigation, A.L., C.C., J.G., J.C., A.B., J.H. and A.V.J.; data curation A.L., C.C., J.G., J.C., A.B., J.H. and A.V.J.; writing—original draft preparation, A.L., C.C., J.G., J.C., A.B., J.H. and A.V.J.; writing—review and editing, all authors; project administration, A.L., C.C. and A.V.J. All authors have read and agreed to the published version of the manuscript.

Funding

No specific funding was received. This work was supported in kind by the institutions of all authors, namely: PathWest Laboratory Medicine WA, Microbiological Diagnostic Unit Public Health Laboratory, University of Melbourne, Institute of Environmental Science and Research Ltd., New Zealand and Public and Environmental Health Reference Laboratories, Pathology Queensland, Queensland Health, The New Zealand component was partially funded by the New Zealand Ministry of Health.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author/s.

Conflicts of Interest

All authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Appendix A. Questions Used to Survey Jurisdictions on Wastewater Surveillance

Survey Questions
Which segments of the survey will you be completing?
Does your jurisdiction undertake SARS-CoV-2 sequencing of wastewater?
Does your jurisdiction issue wastewater reports?
What is the name of the unit/service that collects the sample?
What method of wastewater collection is used for general surveillance?
Does the method vary between sites? Please explain.
From how many sites are samples collected?
How many sites of wastewater treatment plants do you collect samples from?
How many times per month do you collect samples from wastewater treatment plants?
How many sites from sewers do you collect samples from?
How many sites from airports do you collect samples from?
How many times per month do you collect samples from airports?
How many sites from facility/building do you collect samples from?
Please indicate the catchment sizes of wastewater treatment plant
Please indicate the catchment sizes of sewer
Please indicate the catchment sizes of facility/building
Which type of sites are samples collected from? Other, please specify
Please indicate the catchment type and sizes.—Other: please specify
What is the make-up of the sites and how often are samples collected?—General population/community
What is the make-up of the sites and how often are samples collected?—Targeted population/community e.g., facility
How many wastewater samples are collected each week for SARS-CoV-2 quantification?
Of these, for how many is sequencing undertaken on?
Are pre-treatments performed on the sample prior to viral concentration (e.g., MgCl2, pre-acidification etc.)? If yes, please state which pre-treatments.
What is the name of the unit/service where viral concentration is performed?
What is the method used for viral concentration?
What volume do you process?
What is the name of the laboratory where RNA extraction is performed?
What extraction platform and kit are used?
Do you use an RNAase inhibitor? If yes, at what stage?
Is quantitative SARS-CoV-2 PCR performed on all samples?
Which RT-qPCR assay is used to perform quantitative SARS-CoV-2 PCR? Please describe.
Is the sample transported to another laboratory after extraction and before amplification/sequencing? If yes, how long after extraction are they transported and what?
What is the name of the laboratory where sequencing is performed?
What sequencing method is used?
What method/scheme is used for amplicon generation/library preparation?
What sequencing platform is used
What is the deconvolution tool for reporting of lineages?
What are the QC criteria to allow reporting of a sample?
Which of the following check controls do you use?
Which components of the workflow have you validated and to what extent?
What are you including in your reporting?
What level are the lineages reported?
If lineages are collapsed, what is your process for doing so?
Who is the intended audience of the report?

References

  1. Parkins Michael, D.; Lee Bonita, E.; Acosta, N.; Bautista, M.; Hubert Casey, R.J.; Hrudey Steve, E.; Frankowski, K.; Pang, X.-L. Wastewater-based surveillance as a tool for public health action: SARS-CoV-2 and beyond. Clin. Microbiol. Rev. 2023, 37, e00103-22. [Google Scholar] [CrossRef] [PubMed]
  2. Sinclair, R.G.; Choi, C.Y.; Riley, M.R.; Gerba, C.P. Pathogen surveillance through monitoring of sewer systems. Adv. Appl. Microbiol. 2008, 65, 249–269. [Google Scholar] [PubMed]
  3. Levy, J.I.; Andersen, K.G.; Knight, R.; Karthikeyan, S. Wastewater surveillance for public health. Science 2023, 379, 26–27. [Google Scholar] [CrossRef] [PubMed]
  4. O’Keeffe, J. Wastewater-based epidemiology: Current uses and future opportunities as a public health surveillance tool. Environ. Health Rev. 2021, 64, 44–52. [Google Scholar] [CrossRef]
  5. Grassly, N.C.; Shaw, A.G.; Owusu, M. Global wastewater surveillance for pathogens with pandemic potential: Opportunities and challenges. Lancet Microbe 2025, 6, 100939. [Google Scholar] [CrossRef] [PubMed]
  6. Diamond, M.B.; Keshaviah, A.; Bento, A.I.; Conroy-Ben, O.; Driver, E.M.; Ensor, K.B.; Halden, R.U.; Hopkins, L.P.; Kuhn, K.G.; Moe, C.L.; et al. Wastewater surveillance of pathogens can inform public health responses. Nat Med. 2022, 28, 1992–1995. [Google Scholar] [CrossRef] [PubMed]
  7. Shrestha, S.; Yoshinaga, E.; Chapagain, S.K.; Mohan, G.; Gasparatos, A.; Fukushi, K. Wastewater-Based Epidemiology for Cost-Effective Mass Surveillance of COVID-19 in Low- and Middle-Income Countries: Challenges and Opportunities. Water 2021, 13, 2897. [Google Scholar] [CrossRef]
  8. Ali, S.; Gudina, E.K.; Gize, A.; Aliy, A.; Adankie, B.T.; Tsegaye, W.; Hundie, G.B.; Muleta, M.B.; Chibssa, T.R.; Belaineh, R.; et al. Community Wastewater-Based Surveillance Can Be a Cost-Effective Approach to Track COVID-19 Outbreak in Low-Resource Settings: Feasibility Assessment for Ethiopia Context. Int. J. Environ. Res. Public Health 2022, 19, 8515. [Google Scholar] [CrossRef]
  9. Leifels, M.; Lee, W.L.; Armas, F.; Gu, X.; Chandra, F.; Cheng, D.; Kwok, W.C.; Chua, F.J.D.; Kim, S.Y.; Ng, W.J.; et al. Surveillance of SARS-CoV-2 in Wastewater at the Population Level: Insights into the Implementation of Non-invasive Targeted Monitoring in Singapore and the USA. In Wastewater Surveillance for COVID-19 Management; Kumar, M., Kuroda, K., Mukherjee, S., Ngiehm, L.D., Vithanage, M., Tyagi, V.K., Eds.; Springer International Publishing: Cham, Switzerland, 2024; pp. 1–20. [Google Scholar]
  10. Hovi, T.; Shulman, L.M.; Van Der Avoort, H.; Deshpande, J.; Roivainen, M.; de Gourville, E.M. Role of environmental poliovirus surveillance in global polio eradication and beyond. Epidemiol. Infect. 2012, 140, 1–13. [Google Scholar] [CrossRef]
  11. Keshaviah, A.; Diamond, M.B.; Wade, M.J.; Scarpino, S.V.; Ahmed, W.; Amman, F.; Aruna, O.; Badilla-Aguilar, A.; Bar-Or, I.; Bergthaler, A.; et al. Wastewater monitoring can anchor global disease surveillance systems. Lancet Glob. Health 2023, 11, e976–e981. [Google Scholar] [CrossRef]
  12. Naughton, C.C.; Roman, F.A., Jr.; Alvarado, A.G.F.; Tariqi, A.Q.; Deeming, M.A.; Kadonsky, K.F.; Bibby, K.; Bivins, A.; Medema, G.; Ahmed, W.; et al. Show us the data: Global COVID-19 wastewater monitoring efforts, equity, and gaps. FEMS Microbes 2023, 4, xtad003. [Google Scholar] [CrossRef]
  13. Gawlik, B.; Tavazzi, S.; Mariani, G.; Skejo, H.; Sponar, M.; Higgins, T.; Medema, G.; Wintgens, T. SARS-CoV-2 Surveillance Employing Sewage—Towards a Sentinel System; European Union Publications Office: Luxembourg, 2021. [Google Scholar]
  14. Michie, A. Wastewater-based SARS-CoV-2 surveillance and sequencing. Microbiol. Aust. 2024, 45, 8–12. [Google Scholar] [CrossRef]
  15. Water Research Australia. Collaboration on Sewage Surveillance of SARS-CoV-2 (ColoSSoS); Water Research Australia: Adelaide, SA, Australia, 2022. [Google Scholar]
  16. Ahmed, W.; Tscharke, B.; Bertsch, P.M.; Bibby, K.; Bivins, A.; Choi, P.; Clarke, L.; Dwyer, J.; Edson, J.; Nguyen, T.M.H.; et al. SARS-CoV-2 RNA monitoring in wastewater as a potential early warning system for COVID-19 transmission in the community: A temporal case study. Sci. Total Environ. 2021, 761, 144216. [Google Scholar]
  17. Randazzo, W.; Truchado, P.; Cuevas-Ferrando, E.; Simón, P.; Allende, A.; Sánchez, G. SARS-CoV-2 RNA in wastewater anticipated COVID-19 occurrence in a low prevalence area. Water Res. 2020, 181, 115942. [Google Scholar] [PubMed]
  18. Medema, G.; Heijnen, L.; Elsinga, G.; Italiaander, R.; Brouwer, A. Presence of SARS-Coronavirus-2 RNA in Sewage and Correlation with Reported COVID-19 Prevalence in the Early Stage of the Epidemic in The Netherlands. Environ. Sci. Technol. Lett. 2020, 7, 511–516. [Google Scholar] [PubMed]
  19. La Rosa, G.; Iaconelli, M.; Mancini, P.; Bonanno Ferraro, G.; Veneri, C.; Bonadonna, L.; Lucentini, L.; Suffredini, E. First detection of SARS-CoV-2 in untreated wastewaters in Italy. Sci. Total Environ. 2020, 736, 139652. [Google Scholar]
  20. Levy, A.; Gazeley, J.; Lee, T.; Jardine, A.; Gordon, C.; Cooper, N.; Theobald, R.; Huppatz, C.; Sjollema, S.; Hodge, M.; et al. Whole genome sequencing of SARS-CoV-2 from wastewater links to individual cases in catchments. Sci. Total Environ. 2022, 851 Pt 2, 158266. [Google Scholar] [CrossRef] [PubMed]
  21. Hewitt, J.; Trowsdale, S.; Armstrong, B.A.; Chapman, J.R.; Carter, K.M.; Croucher, D.M.; Trent, C.R.; Sim, R.E.; Gilpin, B.J. Sensitivity of wastewater-based epidemiology for detection of SARS-CoV-2 RNA in a low prevalence setting. Water Res. 2022, 211, 118032. [Google Scholar] [PubMed]
  22. McMahan, C.S.; Self, S.; Rennert, L.; Kalbaugh, C.; Kriebel, D.; Graves, D.; Colby, C.; Deaver, J.A.; Popat, S.C.; Karanfil, T.; et al. COVID-19 wastewater epidemiology: A model to estimate infected populations. Lancet Planet. Health 2021, 5, e874–e881. [Google Scholar]
  23. Gazeley, J.; Lee, T.; Knight, D.R.; Shivarev, A.; Gordon, C.; Speers, D.; Barth, D.D.; Maticevic, J.; Hodge, M.; Armstrong, P.; et al. Correlating Quantitative and Genomic SARS-CoV-2 Wastewater Data with Clinical Metrics in Metropolitan Perth, Western Australia. Environments 2024, 11, 62. [Google Scholar] [CrossRef]
  24. Crits-Christoph, A.; Kantor, R.S.; Olm, M.R.; Whitney, O.N.; Al-Shayeb, B.; Lou, Y.C.; Flamholz, A.; Kennedy, L.C.; Greenwald, H.; Hinkle, A.; et al. Genome Sequencing of Sewage Detects Regionally Prevalent SARS-CoV-2 Variants. mBio 2021, 12, 1. [Google Scholar] [CrossRef]
  25. Karthikeyan, S.; Levy, J.I.; De Hoff, P.; Humphrey, G.; Birmingham, A.; Jepsen, K.; Farmer, S.; Tubb, H.M.; Valles, T.; Tribelhorn, C.E.; et al. Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission. Nature 2022, 609, 101–108. [Google Scholar] [CrossRef] [PubMed]
  26. Herold, M.; d’Hérouël, A.F.; May, P.; Delogu, F.; Wienecke-Baldacchino, A.; Tapp, J.; Walczak, C.; Wilmes, P.; Cauchie, H.-M.; Fournier, G.; et al. Genome Sequencing of SARS-CoV-2 Allows Monitoring of Variants of Concern through Wastewater. Water 2021, 13, 3018. [Google Scholar] [CrossRef]
  27. Merrett, J.E.; Nolan, M.; Hartman, L.; John, N.; Flynn, B.; Baker, L.; Schang, C.; McCarthy, D.; Lister, D.; Cheng, N.N.; et al. Highly sensitive wastewater surveillance of SARS-CoV-2 variants by targeted next-generation amplicon sequencing provides early warning of incursion in Victoria, Australia. Appl. Environ. Microbiol. 2024, 90, e01497-23. [Google Scholar]
  28. The Institute of Environmental Science and Research. Wastewater COVID-19 Surveillance 2025 [Updated 6 March 2025]. Available online: https://www.poops.nz/ (accessed on 13 March 2025).
  29. Wu, F.; Lee, W.L.; Chen, H.; Gu, X.; Chandra, F.; Armas, F.; Xiao, A.; Leifels, M.; Rhode, S.F.; Wuertz, S.; et al. Making waves: Wastewater surveillance of SARS-CoV-2 in an endemic future. Water Res. 2022, 219, 118535. [Google Scholar]
  30. Communicable Diseases Network Australia (CDNA). SARS-CoV-2 Wastewater Surveillance CDNA National Strategy; Australian Government—Department of Health and Aged Care: Canberra, ACT, Australia, 2022.
  31. Smith, M.F.; Holland, S.C.; Lee, M.B.; Hu, J.C.; Pham, N.C.; Sullins, R.A.; Holland, L.A.; Mu, T.; Thomas, A.W.; Fitch, R.; et al. Baseline Sequencing Surveillance of Public Clinical Testing, Hospitals, and Community Wastewater Reveals Rapid Emergence of SARS-CoV-2 Omicron Variant of Concern in Arizona, USA. mBio 2023, 14, e03101-22. [Google Scholar] [PubMed]
  32. Vo, V.; Tillett, R.L.; Papp, K.; Shen, S.; Gu, R.; Gorzalski, A.; Siao, D.; Markland, R.; Chang, C.-L.; Baker, H.; et al. Use of wastewater surveillance for early detection of Alpha and Epsilon SARS-CoV-2 variants of concern and estimation of overall COVID-19 infection burden. Sci. Total Environ. 2022, 835, 155410. [Google Scholar] [PubMed]
  33. Espinosa-Gongora, C.; Berg, C.; Rehn, M.; Varg, J.E.; Dillner, L.; Latorre-Margalef, N.; Székely, A.J.; Andersson, E.; Movert, E. Early detection of the emerging SARS-CoV-2 BA.2.86 lineage through integrated genomic surveillance of wastewater and COVID-19 cases in Sweden, weeks 31 to 38 2023. Eurosurveillance 2023, 28, 2300595. [Google Scholar] [PubMed]
  34. Health Emergency Preparedness and Response Authority. Launching GLOWACON: A Global Initiative for Wastewater Surveillance for Public Health; European Commission—Public Health: Brussels, Belgium, 2024.
  35. Council of the EU. Urban Wastewater: Council Adopts New Rules for More Efficient Treatment; European Council—Council of the European Union: Brussels, Belgium, 2024.
  36. National Academies of Sciences, Engineering, and Medicine. Increasing the Utility of Wastewater-Based Disease Surveillance for Public Health Action: A Phase 2 Report; National Academies Press: Washington, DC, USA, 2024. [Google Scholar]
  37. Adams, C.; Bias, M.; Welsh, R.M.; Webb, J.; Reese, H.; Delgado, S.; Person, J.; West, R.; Shin, S.; Kirby, A. The National Wastewater Surveillance System (NWSS): From inception to widespread coverage, 2020–2022, United States. Sci. Total Environ. 2024, 924, 171566. [Google Scholar] [CrossRef]
  38. United Nations. WHO Chief Declares End to COVID-19 as a Global Health Emergency. 2023. Available online: https://news.un.org/en/story/2023/05/1136367 (accessed on 13 March 2025).
  39. World Health Organization. WHO Director-General’s Opening Remarks at the Media Briefing—5 May 2023; World Health Organization: Geneva, Switzerland, 2023. [Google Scholar]
  40. Servetas, S.L.; Parratt, K.H.; Brinkman, N.E.; Shanks, O.C.; Smith, T.; Mattson, P.J.; Lin, N.J. Standards to support an enduring capability in wastewater surveillance for public health: Where are we? Case Stud. Chem. Environ. Eng. 2022, 6, 100247. [Google Scholar]
  41. Lu, D.; Huang, Z.; Luo, J.; Zhang, X.; Sha, S. Primary concentration—The critical step in implementing the wastewater based epidemiology for the COVID-19 pandemic: A mini-review. Sci. Total Environ. 2020, 747, 141245. [Google Scholar] [CrossRef]
  42. Ahmed, W.; Bivins, A.; Bertsch, P.M.; Bibby, K.; Choi, P.M.; Farkas, K.; Gyawali, P.; Hamilton, K.A.; Haramoto, E.; Kitajima, M.; et al. Surveillance of SARS-CoV-2 RNA in wastewater: Methods optimization and quality control are crucial for generating reliable public health information. Curr. Opin. Environ. Sci. Health 2020, 17, 82–93. [Google Scholar] [CrossRef] [PubMed]
  43. Ahmed, W.; Simpson, S.L.; Bertsch, P.M.; Bibby, K.; Bivins, A.; Blackall, L.L.; Bofill-Mas, S.; Bosch, A.; Brandão, J.; Choi, P.M.; et al. Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance. Sci. Total Environ. 2022, 805, 149877. [Google Scholar] [CrossRef] [PubMed]
  44. Kumblathan, T.; Liu, Y.; Uppal, G.K.; Hrudey, S.E.; Li, X.-F. Wastewater-Based Epidemiology for Community Monitoring of SARS-CoV-2: Progress and Challenges. ACS Environ. Au 2021, 1, 18–31. [Google Scholar] [CrossRef] [PubMed]
  45. Williams, R.C.; Perry, W.B.; Lambert-Slosarska, K.; Futcher, B.; Pellett, C.; Richardson-O’Neill, I.; Paterson, S.; Grimsley, J.M.; Wade, M.J.; Weightman, A.J.; et al. Examining the stability of viral RNA and DNA in wastewater: Effects of storage time, temperature, and freeze-thaw cycles. Water Res. 2024, 259, 121879. [Google Scholar] [CrossRef] [PubMed]
  46. Ferdous, J.; Kunkleman, S.; Taylor, W.; Harris, A.; Gibas, C.J.; Schlueter, J.A. A gold standard dataset and evaluation of methods for lineage abundance estimation from wastewater. Sci. Total Environ. 2024, 948, 174515. [Google Scholar] [CrossRef] [PubMed]
  47. World Health Organization. Updated Working Definitions and Primary Actions for SARS-CoV-2 Variants; World Health Organization: Geneva, Switzerland, 2023. [Google Scholar]
  48. Baaijens, J.A.; Zulli, A.; Ott, I.M.; Nika, I.; van der Lugt, M.J.; Petrone, M.E.; Alpert, T.; Fauver, J.R.; Kalinich, C.C.; Vogels, C.B.F.; et al. Lineage abundance estimation for SARS-CoV-2 in wastewater using transcriptome quantification techniques. Genome Biol. 2022, 23, 236. [Google Scholar] [CrossRef] [PubMed]
  49. Yu, A.T.; Hughes, B.; Wolfe, M.K.; Leon, T.; Duong, D.; Rabe, A.; Kennedy, L.C.; Ravuri, S.; White, B.J.; Wigginton, K.R.; et al. Estimating Relative Abundance of 2 SARS-CoV-2 Variants through Wastewater Surveillance at 2 Large Metropolitan Sites, United States. Emerg. Infect. Dis. 2022, 28, 940–947. [Google Scholar] [CrossRef] [PubMed]
  50. Timme, R.E.; Woods, J.; Jones, J.L.; Calci, K.R.; Rodriguez, R.; Barnes, C.; Leard, E.; Craven, M.; Chen, H.; Boerner, C.; et al. SARS-CoV-2 wastewater variant surveillance: Pandemic response leveraging FDA’s GenomeTrakr network. mSystems 2024, 9, e01415-23. [Google Scholar] [CrossRef]
  51. Rakeman-Cagno, J.L.; Persing, D.H.; Loeffelholz, M.J. Maintaining point of care testing capacity and pandemic preparedness in the post-COVID-19 era. Expert Rev. Mol. Diagn. 2024, 24, 147–151. [Google Scholar] [CrossRef]
  52. Karami, H.; Soleimani, M.; Nayerain Jazi, N.; Navi, K.; Sajadi, R.; Fazeli, M.M.; Pagheh, G.; Dehkordi, S.O. The next viral pandemic: A call for global preparedness. J. Med. Surg. Public Health 2024, 4, 100150. [Google Scholar] [CrossRef]
  53. Yamey, G.; Schäferhoff, M.; Aars, O.K.; Bloom, B.; Carroll, D.; Chawla, M.; Dzau, V.; Echalar, R.; Gill, I.S.; Godal, T.; et al. Financing of international collective action for epidemic and pandemic preparedness. Lancet Glob. Health 2017, 5, e742–e744. [Google Scholar] [CrossRef] [PubMed]
  54. Valencia, D.; Yu, A.T.; Wheeler, A.; Hopkins, L.; Pray, I.; Horter, L.; Vugia, D.J.; Matzinger, S.; Stadler, L.; Kloczko, N.; et al. Notes from the Field: The National Wastewater Surveillance System’s Centers of Excellence Contributions to Public Health Action During the Respiratory Virus Season—Four U.S. Jurisdictions, 2022–2023. MMWR Morb. Mortal. Wkly. Rep. 2023, 72, 1309–1312. [Google Scholar] [CrossRef]
  55. Korfmacher, K.S.; Harris-Lovett, S.; Nelson, K.L. Campus Collaborations As a Model for Transforming SARS-CoV-2 Wastewater Surveillance Research into Public Health Action. Environ. Sci. Technol. 2021, 55, 12770–12772. [Google Scholar] [CrossRef] [PubMed]
  56. Hill, D.T.; Alazawi, M.A.; Moran, E.J.; Bennett, L.J.; Bradley, I.; Collins, M.B.; Gobler, C.J.; Green, H.; Insaf, T.Z.; Kmush, B.; et al. Wastewater surveillance provides 10-days forecasting of COVID-19 hospitalizations superior to cases and test positivity: A prediction study. Infect. Dis. Model. 2023, 8, 1138–1150. [Google Scholar] [CrossRef] [PubMed]
  57. Sheth, K.; Domakonda, K.; Short, K.; Stadler, L.; Ensor, K.B.; Johnson, C.D.; Williams, S.L.; Persse, D.; Hopkins, L. A Novel Framework for Internal Responses to Detection of Pathogens in Wastewater by Public Health Agencies. Public Health Rep. 2024, 140, 22–31. [Google Scholar] [CrossRef]
  58. Brosky, H.; Prasek, S.M.; Innes, G.K.; Pepper, I.L.; Miranda, J.; Brierley, P.E.; Slinski, S.L.; Polashenski, L.; Betancourt, W.Q.; Gronbach, K.; et al. A framework for integrating wastewater-based epidemiology and public health. Front. Public Health 2024, 12, 1418681. [Google Scholar] [CrossRef]
  59. Keshaviah, A.; Akram, A.; Rizmie, D.; Raxter, I.; Hasan, R.; Rahman, Z.; Jannat Suchana, A.; Jahan, F.; Rahman, A.; Rahman, M.; et al. A cost-benefit analysis of using wastewater monitoring to guide typhoid vaccine campaigns. Res. Sq. 2025; preprint. [Google Scholar] [CrossRef]
  60. Yoo, B.-K.; Iwamoto, R.; Chung, U.; Sasaki, T.; Kitajima, M. Economic Evaluation of Wastewater Surveillance Combined with Clinical COVID-19 Screening Tests, Japan. Emerg. Infect. Dis. 2023, 29, 1608–1617. [Google Scholar] [CrossRef]
  61. Foxman, B.; Salzman, E.; Gesierich, C.; Gardner, S.; Ammerman, M.; Eisenberg, M.; Wigginton, K. Wastewater surveillance of antibiotic resistant bacteria for public health action: Potential and Challenges. Am. J. Epidemiol. 2024, kwae419. [Google Scholar] [CrossRef]
  62. EU-WISH. Wastewater Surveillance of Antimicrobial Resistance Across Europe; EU-WISH: Online, 2025; Available online: https://www.eu-wish.eu/results?tx_news_pi1%5Baction%5D=detail&tx_news_pi1%5Bcontroller%5D=News&tx_news_pi1%5Bnews%5D=19&cHash=ee2b748d6620c0e1672128f8829f01ad (accessed on 26 March 2025).
  63. Qian, Q.; Fan, L.; Liu, W.; Li, J.; Yue, J.; Wang, M.; Ke, X.; Yin, Y.; Chen, Q.; Jiang, C. Direct Evidence of Active SARS-CoV-2 Replication in the Intestine. Clin. Infect. Dis. 2021, 73, 361–366. [Google Scholar] [CrossRef] [PubMed]
  64. Zhang, H.; Kang, Z.; Gong, H.; Xu, D.; Wang, J.; Li, Z.; Li, Z.; Cui, X.; Xiao, J.; Zhan, J.; et al. Digestive system is a potential route of COVID-19: An analysis of single-cell coexpression pattern of key proteins in viral entry process. Gut 2020, 69, 1010. [Google Scholar]
  65. Ciesielski, M.; Blackwood, D.; Clerkin, T.; Gonzalez, R.; Thompson, H.; Larson, A.; Noble, R. Assessing sensitivity and reproducibility of RT-ddPCR and RT-qPCR for the quantification of SARS-CoV-2 in wastewater. J. Virol. Methods 2021, 297, 114230. [Google Scholar] [PubMed]
  66. Ahmed, W.; Smith, W.J.M.; Metcalfe, S.; Jackson, G.; Choi, P.M.; Morrison, M.; Field, D.; Gyawali, P.; Bivins, A.; Bibby, K.; et al. Comparison of RT-qPCR and RT-dPCR Platforms for the Trace Detection of SARS-CoV-2 RNA in Wastewater. ACS ES&T Water 2022, 2, 1871–1880. [Google Scholar]
  67. Ding, J.; Xu, X.; Deng, Y.; Zheng, X.; Zhang, T. Comparison of RT-ddPCR and RT-qPCR platforms for SARS-CoV-2 detection: Implications for future outbreaks of infectious diseases. Environ. Int. 2024, 183, 108438. [Google Scholar] [PubMed]
  68. Robins, K.; Leonard, A.F.C.; Farkas, K.; Graham, D.W.; Jones, D.L.; Kasprzyk-Hordern, B.; Bunce, J.T.; Grimsley, J.M.S.; Wade, M.J.; Zealand, A.M.; et al. Research needs for optimising wastewater-based epidemiology monitoring for public health protection. J. Water Health 2022, 20, 1284–1313. [Google Scholar] [CrossRef]
  69. NSF Research Coordination Network. Wastewater Surveillance for SARS-CoV-2 and Emerging Public Health Threats. Available online: https://sites.nd.edu/rcn-wastewater-sarscov2/ (accessed on 13 March 2025).
  70. The Global Health Network—ODIN. Environmental and Wastewater Surveillance (EWS) Community of Practice and knowledge Exchange. 2025. Available online: https://odin-wsp.tghn.org/odin-consortium/unikin/ (accessed on 13 March 2025).
  71. Water Research Australia. Tag Archives: WBE Community of Practice. Available online: https://www.waterra.com.au/tag/wbe-community-of-practice/ (accessed on 13 March 2025).
  72. Communicable Diseases Genomics Network (CDGN). Working Groups—CDGN Working Groups. Available online: https://www.cdgn.org.au/working-groups (accessed on 13 March 2025).
  73. Minister for Health and Aged Care and Treasurer, Press Conference—29 October 2024 [Press Release]. 29 October 2024. Available online: https://www.health.gov.au/ministers/the-hon-mark-butler-mp/media/minister-for-health-and-aged-care-and-treasurer-press-conference-29-october-2024 (accessed on 13 March 2025).
  74. New Zealand Ministry of Business Innovation and Employment. Refocusing the Science, Innovation and Technology System. Online. 2025. Available online: https://www.mbie.govt.nz/science-and-technology/science-and-innovation/agencies-policies-and-budget-initiatives/refocusing-the-science-innovation-and-technology-system (accessed on 13 March 2025).
  75. Xiao, K.; Zhang, L. Wastewater pathogen surveillance based on One Health approach. Lancet Microbe 2023, 4, e297. [Google Scholar] [CrossRef] [PubMed]
  76. Hill, R.; Stentiford, G.D.; Walker, D.I.; Baker-Austin, C.; Ward, G.; Maskrey, B.H.; van Aerle, R.; Verner-Jeffreys, D.; Peeler, E.; Bass, D. Realising a global One Health disease surveillance approach: Insights from wastewater and beyond. Nat. Commun. 2024, 15, 5324. [Google Scholar] [CrossRef] [PubMed]
  77. Leifels, M.; Rahman, O.K.; Sam, I.-C.; Cheng, D.; Chua, F.J.D.; Nainani, D.; Kim, S.Y.; Ng, W.J.; Kwok, W.C.; Sirikanchana, K.; et al. The one health perspective to improve environmental surveillance of zoonotic viruses: Lessons from COVID-19 and outlook beyond. ISME Commun. 2022, 2, 107. [Google Scholar] [CrossRef] [PubMed]
  78. Yoo, B.-K.; Goto, R.; Kitajima, M.; Sasaki, T.; Himmler, S. Willingness to pay for nationwide wastewater surveillance system for infectious diseases in Japan. Environ. Sci. Water Res. Technol. 2025, 11, 29–38. [Google Scholar]
  79. Morales, D.; Rhodes, T.; O’Reilly, K. Stakeholder Interviews to Inform Best Practice for Public Facing COVID-19 Wastewater Dashboards [version 1; peer review: 2 approved with reservations]. Gates Open Res. 2024, 8, 61. [Google Scholar] [CrossRef]
  80. Parkinson, S.; Dawney, J.; Adams, A.; Senator, B. Data Collection and Sharing for Pathogen Surveillance: Making Sense of a Fragmented Global System. RAND Health Q. 2024, 11, 4. [Google Scholar] [PubMed]
Table 1. Summary of jurisdictional responses for key wastewater processing elements.
Table 1. Summary of jurisdictional responses for key wastewater processing elements.
Key ProcessNumber of Jurisdictions or Process Metric/Number of Responses
Sampling by single water utility4/8
Use of composite auto-sampling5/8
Use of passive samplers3/8
Fewer than 10 sampling locations5/8
Only collected from treatment plants5/8
Airport included in catchment site2/8
Treatment plant catchment population size50,000–2,000,000
Concentration by electronegative membrane filtration6/7
Concentration by polyethylene glycol precipitation1/7
Volume concentrated 50–250 mL
Use of the ThermoFisher MagMAX Microbiome Ultra extraction kit4/7
Purification by semi-automated magnetic bead platform4/7
Purification by silica spin column method4/7
Use of RNase inhibitor4/7
RT-PCR targeting nucleocapsid gene used5/7
Quantitative real-time RT-PCR used5/7
Validated PCR method in use3/6
DNA sequencing performed5/8
Whole genome tiled amplicon (Illumina) sequencing performed4/7
Inclusion of negative controls in sequencing4/6
SARS-CoV-2 lineage relative abundance determined5/6
Direct comparison of wastewater sequencing with clinical case lineages3/6
Data publicly available via online dashboard2/6
Table 2. Summary of controls reported by five jurisdictions.
Table 2. Summary of controls reported by five jurisdictions.
ControlNumber Jurisdictions
Negative concentration control3
Negative extraction control3
Internal process control at extraction step2
Positive PCR control3
Internal process control at PCR step2
Negative sequencing control5
Positive sequencing control1
Table 3. Summary of SARS-CoV-2 municipal wastewater samples sequenced per week and method used.
Table 3. Summary of SARS-CoV-2 municipal wastewater samples sequenced per week and method used.
JurisdictionNumber of Samples Tested by PCR per WeekNumber of Samples Sequenced per Week (Proportion)Sequencing Method
A44 (100%)WGS
B31.5 * (50%)WGS
C106 (60%)amplicon
D63 (50%)WGS
E1919 ** (100%)amplicon + WGS
F4520 (44%)amplicon
G150 (0%)NA
WGS—whole genome sequencing, NA—not applicable. * Three samples sequenced per fortnight. ** Maximum. Only samples with N-gene qPCR Ct < 37 sequenced.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Levy, A.; Crachi, C.; Gazeley, J.; Chapman, J.; Brischetto, A.; Speers, D.; Hewitt, J.; Jennison, A.V.; The Wastewater Surveillance Working Group, Communicable Diseases Genomics Network of Australia. Australian and New Zealand Laboratory Experience and Proposed Future Direction of Wastewater Pathogen Genomic Surveillance. Environments 2025, 12, 114. https://doi.org/10.3390/environments12040114

AMA Style

Levy A, Crachi C, Gazeley J, Chapman J, Brischetto A, Speers D, Hewitt J, Jennison AV, The Wastewater Surveillance Working Group, Communicable Diseases Genomics Network of Australia. Australian and New Zealand Laboratory Experience and Proposed Future Direction of Wastewater Pathogen Genomic Surveillance. Environments. 2025; 12(4):114. https://doi.org/10.3390/environments12040114

Chicago/Turabian Style

Levy, Avram, Christina Crachi, Jake Gazeley, Joanne Chapman, Anna Brischetto, David Speers, Joanne Hewitt, Amy V. Jennison, and The Wastewater Surveillance Working Group, Communicable Diseases Genomics Network of Australia. 2025. "Australian and New Zealand Laboratory Experience and Proposed Future Direction of Wastewater Pathogen Genomic Surveillance" Environments 12, no. 4: 114. https://doi.org/10.3390/environments12040114

APA Style

Levy, A., Crachi, C., Gazeley, J., Chapman, J., Brischetto, A., Speers, D., Hewitt, J., Jennison, A. V., & The Wastewater Surveillance Working Group, Communicable Diseases Genomics Network of Australia. (2025). Australian and New Zealand Laboratory Experience and Proposed Future Direction of Wastewater Pathogen Genomic Surveillance. Environments, 12(4), 114. https://doi.org/10.3390/environments12040114

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop