Aims: The wider implementation of wastewater-based surveillance (WBS) has increased the necessity for nucleic acid detection and quantification from complex samples. Here, we compared the performance and the characteristics of three digital polymerase chain reaction (dPCR) platforms.
Methods and results: The dPCR platforms selected in this study included the QX200 AutoDG Droplet Digital PCR System from Bio-Rad, the QIAcuity One, 2plex Device from Qiagen, and the 3-color Naica System manufactured by Stilla Technologies. Platforms were compared and described based on their handling in the laboratory and performance quantifying two viral targets—SARS-CoV-2 and Norovirus GII—in wastewater samples. Our findings showed that no single platform consistently outperformed the others in terms of target quantification. Moreover, we observed similarities amongst the systems with respect to resilience to inhibition, but differences in laboratory handling including sample throughput and method of quantification.
Conclusions: This study suggests that all three selected dPCR platforms are similarly suitable for WBS, as quantitative performance of the systems for viral RNA targets extracted from wastewater is comparable. Decisions on platform selection can be driven by researcher preference on handling, throughput, and other differentiating characteristics. Impact Statement This study contributes to the field of environmental virology by showing the compatibility and reliability of three dPCR platforms for WBS. By comparing the platforms’ performance in detecting two viral targets, the research provides insights into their operational strengths and weaknesses.

Wastewater surveillance can track trends in multiple pathogens simultaneously by leveraging efficient laboratory processing. In Switzerland, wastewater surveillance of four respiratory pathogens is conducted at 14 locations representing 2.3 million people. Trends in respiratory diseases are tracked using a six-plex digital PCR assay targeting influenza A, influenza B, respiratory syncytial virus and SARS-CoV-2 N1 and N2 regions and murine hepatitis virus for recovery efficiency control. Wastewater data were integrated with disease data from two reporting systems, and comparisons from July 2023 to July 2024 showed strong agreement for most targets. Lower correspondence for influenza B highlighted challenges in tracking disease dynamics during seasons without pronounced outbreaks. Wastewater monitoring further revealed that targeting N1 or N2 led to divergent estimates of SARS-CoV-2 loads, highlighting the impact of mutations in assay target regions. The study emphasizes the importance of an integrated wastewater monitoring programme as a complementary tool for public health surveillance, demonstrating clear concordance with clinical data.

As more data on virus concentrations in influent water from wastewater treatment plants (WWTPs) becomes available, establishing best practices for virus measurements, monitoring, and statistical modelling can improve the understanding of virus concentration distributions in wastewater. To support this, we assessed the temporal variability of norovirus, adenovirus, enterovirus, and rotavirus concentrations in influent water across multiple WWTPs in Switzerland, the USA, and Japan. Our findings demonstrate that the lognormal distribution accurately describes temporal variations in concentrations for all viruses at all sites, outperforming the gamma and Weibull distributions, which fail to capture high variability. However, notable differences in variability and uncertainty were observed across systems, underscoring the need for site-specific assessments. Using lognormal parameters, we identified optimal monitoring frequencies that balance cost-effectiveness and precision. For most sites, weekly monitoring was sufficient to estimate the annual average concentration of enteric viruses within a 95% confidence interval of 0.5 log₁₀. We further examined the mechanistic basis of the lognormal distribution, highlighting processes that drive its prevalence and shape the behavior of its upper tail. By integrating these insights, this study provides a statistical foundation for optimizing virus monitoring frameworks and informing public health interventions targeting wastewater systems.

Noroviruses and enteroviruses are major causes of endemic gastrointestinal disease associated with substantial disease burden. However, viral gastroenteritis is often diagnosed based on symptoms, with etiology infrequently tested or reported, so little information exists on community-level transmission dynamics. In this study, we demonstrate that norovirus (NoV) genogroup II and enterovirus (EV) viral loads in wastewater reveal transmission dynamics of these viruses. We report NoV and EV concentrations in wastewater from 363 samples between December 5 2020 and October 10 2022 (sampled every second day). Virus concentrations in wastewater were low during 2021, and increased in 2022. Wastewater recapitulated periods of increased clinical cases, and also identified silent waves of transmission. We used the measured wastewater loads to estimate the effective reproductive number (R_e). The R_e for both NoV and EV peaked between 1.1 and 1.2. However, the usual seasonality of NoV transmission was upended by non-pharmaceutical interventions implemented to mitigate the COVID-19 pandemic, leading to correlated transmission dynamics of NoV GII and EV during 2021–2022. This highlights the use of wastewater to understand transmission dynamics of endemic enteric viruses and estimate relevant epidemiological parameters, including R_e.

Safe laboratory processing requires mitigating risks from the release of pathogens into the environment through generated waste streams. This study evaluated the inactivation kinetics of bacteriophage MS2 as a surrogate for infectious viruses in liquid waste produced from total nucleic acid extractions of wastewater. The goal was to determine a waste handling protocol that ensures sufficient viral infectivity loss (i.e., inactivation) for safe disposal. Liquid waste was generated using a viral total nucleic acid extraction kit (Wizard® Enviro Total Nucleic Acid Kit, Promega, The United States of America) containing guanidinium chloride, isopropanol, ethanol, and other residual reagents. MS2 phage was artificially added into liquid waste, and inactivation was monitored over 24 h using double agar layer plaque assays. A one-phase exponential decay model was applied to estimate the time required for safe disposal, showing MS2 inactivation followed an exponential decay pattern, achieving a predicted 6-log₁₀ reduction at an average of 2.41 h (145 min), with a 95% confidence interval of 1.34 h (80 min) to 4.05 h (243 min). However, only the 24-hour holding time was observed to significantly exceed the 6-log₁₀ reduction threshold, supporting its recommendation as a conservative and practical holding time after which the waste can be safely disposed of as chemical solvent waste without additional decontamination measures such as autoclaving, as viral infectivity is reduced by at least 6-log₁₀.

The COVID-19 pandemic has accelerated the development and adoption of wastewater-based epidemiology. Wastewater samples can provide genomic information for detecting and assessing the spread of SARS-CoV-2 variants in communities and for estimating important epidemiological parameters such as the selection advantage of a viral variant. However, despite demonstrated successes, epidemiological data derived from wastewater suffers from potential biases. Of particular concern are shedding profiles, which can affect the relationship between true viral incidence and viral loads in wastewater. Changes in shedding between variants may decouple the established relationship between wastewater loads and clinical test data. Using mathematical modeling, simulations, and Swiss surveillance data, we demonstrate that estimates of the selection advantage of a variant are not biased by shedding profiles. We show that they are robust to differences in shedding between variants under a wide range of assumptions, and identify specific conditions under which this robustness may break down. Additionally, we demonstrate that differences in shedding only briefly affect estimates of the effective reproduction number. Thus, estimates of selective advantage and reproduction numbers derived from wastewater maintain their advantages over traditional clinical data, even when there are differences in shedding among variants.

Objective: While wastewater-based surveillance (WBS) has informed our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza and respiratory syncytial virus (RSV) circulation in the community, its use in hospital settings remains limited. We aimed to use WBS to understand the dynamics between SARS-CoV-2, influenza (A/B) and RSV loads in the hospital wastewater and infections among patients in a geriatric hospital in Switzerland.
Methods: We conducted a prospective WBS study which involved the collection of 24-h composite samples 7 days/week from the centralised hospital wastewater of the geriatric hospital. We measured SARS-CoV-2, influenza A/B and RSV RNA concentrations using digital reverse transcription polymerase chain reaction. Kendall's rank correlation (τ) and cross-correlation function were used to assess the correlation and lag time between the viral RNA loads and SARS-CoV-2, influenza A/B and RSV infections among hospitalised patients.
Results: Between 14^th October 2024 and 19^th April 2025, we collected 166 wastewater samples. The associations between wastewater loads and infections were significant and positive for SARS-CoV-2 (τ = 0.29, 95% confidence interval [CI]: 0.19–0.39, P < 0.01), influenza A (τ = 0.36, 95% CI: 0.25–0.44, P < 0.01) and RSV (τ = 0.48, 95% CI: 0.38–0.57, P < 0.01). In sensitivity analyses restricted to healthcare-associated infections, the associations between wastewater loads and infections among patients remained significant and positive for SARS-CoV-2 (τ = 0.32, 95% CI: 0.23–0.41, P < 0.01), influenza A (τ = 0.24, 95% CI: 0.12–0.34, P < 0.01) and RSV (τ = 0.37, 95% CI: 0.27–0.47, P < 0.01). Increases in wastewater viral load preceded increases in reported SARS-CoV-2 and influenza A healthcare-associated infections by approximately three and five days, respectively.
Conclusions: WBS could be used as a complementary early warning system for the circulation of respiratory viruses in hospital settings.

Measles outbreaks remain a significant public health challenge, despite high vaccination coverage in many regions. Wastewater-based surveillance (WBS) offers a noninvasive and community-level approach to monitoring the circulation of pathogens, including the measles virus. Here, we retrospectively applied a duplex digital PCR assay to distinguish between wild-type and vaccine strains of the measles virus in wastewater samples available from an existing national WBS program. Samples originated from the wastewater treatment plant serving the Lausanne city catchment area, where an outbreak occurred before spreading to the broader Canton Vaud region. Despite high vaccination rates, viral loads of the measles wild type were detected during the first transmission event involving 21 cases identified within a week. However, viral loads were no longer detectable after the initial 21 cases, despite an additional 30 cases reported in the following 3 weeks, possibly due to lower incidence rate or location outside the catchment. Measles vaccine strain was not detected during the outbreak. Our results demonstrate the complementarity of WBS with clinical surveillance and suggest its potential as an early warning system for measles and other vaccine-preventable diseases. Further improvements in the assay sensitivity and integration with epidemiological data could enhance the utility of WBS for outbreak detection and control.

Measles, mumps, and rubella are highly contagious viral diseases that can cause severe health complications, particularly in children and the elderly. To reduce risks, vaccination with the Measles, Mumps, Rubella (MMR) vaccine is recommended, however outbreaks can still occur in communities, particularly those with lagging vaccination coverage. A recent example occurred from January to March 2024 in Lausanne when a measles outbreak emerged involving 51 identified cases. To help support Switzerland’s strategy to monitor and track these three pathogens, we have developed two duplex digital PCR (dPCR) assays for wastewater screening based on previously published assays. The assays targeting: i) measles wild type (WT) and measles vaccine (VA) strains, and ii) mumps and rubella. In this report, we describe the development and validation of the two dPCR assays. The measles WT/VA assay was further applied retrospectively on wastewater extracts collected during the 2024 outbreak in Lausanne. Our findings showed that wastewater viral loads were temporally associated with clinical case data. The developed assays can be implemented to complement clinical-based surveillance, supporting a rapid response to outbreaks, tracking of relative changes, and helping to inform mitigation strategies.

Poliovirus is the causative agent of poliomyelitis, a potentially debilitating disease that is a target for global eradication. Vaccination against poliomyelitis is an important tool in the eradication effort, but one of the available vaccines, the oral poliovirus vaccine, contains live, attenuated strains that can revert to virulent forms. Community transmission of so-called vaccine-derived polioviruses (VDPVs) can contribute to outbreaks, including in areas with no recently reported poliomyelitis cases. Wastewater-based surveillance (WBS) is a widely applied method to monitor communities for outbreaks through the detection and characterization of VDPVs in wastewater including sewage. Results of WBS can help to target interventions, such as increased vaccination efforts. Switzerland is a Polio-Free country, with no evidence of community circulation of poliomyelitis. However, Polio-Free countries remain at risk of importation of wild poliovirus and VDPVs. This document has two parts: Part I describes the development of a digital PCR pan-poliovirus assay to screen wastewater for the presence of poliovirus. Our pan-poliovirus assay has been sufficiently developed to allow application when required. In Part II, the need to further characterize detected poliovirus through strain-specific differentiation assays is discussed. A literature review of available differentiation assays complements this part. Together, the report documents wet-lab methodological approaches to implement poliovirus screening in wastewater within the scope of the ongoing WBS methods targeting respiratory viruses (Influenza A, Influenza B, SARS-CoV-2, and Respiratory Syncytial Virus) and offers a resource to help aid response and surveillance decisions.

Quantitative polymerase chain reaction (qPCR) and digital PCR (dPCR) are applied for quantifying molecular targets in disease diagnostics, pathogen detection, and ecological monitoring. Uptake of dPCR is increasing due to its higher quantification accuracy relative to qPCR, which stems from its independence from standard curves and its increased resistance to PCR inhibitors. Throughput can be increased through multiplexing, which allows simultaneous quantification of multiple targets. However, multiplexing with dPCR faces unique challenges relative to qPCR. Here, we describe the three-phase development process of non-competing multiplex dPCR assays using target-specific fluorescently labeled hydrolysis probes. We highlight common challenges encountered, along with recommended solutions. Phase 1: In silico assay design; target-specific primers and probes are selected or designed, potential issues with primer and probe interactions are identified, and fluorophores and quenchers are chosen based on dPCR instrumentation. Phase 2: Wet-lab validation; assays are benchmarked using positive controls. Insufficient performance leads to assay redesign, as needed. Phase 3: Assay implementation; assay specificity and sensitivity are validated on relevant sample matrices. Finally, we provide recommendations on the future design and standardization of multiplexed dPCR assays, highlighting the need for better in silico predictions of assay performance, standardizing positive controls, and automating partition classification systems.

Wastewater-based epidemiology offers a complementary approach to clinical case-based surveillance of emergent diseases and can help identify regions with infected people to prioritize clinical surveillance strategies. However, tracking emergent diseases in wastewater requires reliance on novel testing assays with uncertain sensitivity and specificity. Limited pathogen shedding may cause detection to be below the limit of quantification or bordering the limit of detection. Here, we investigated how the definition of limit of detection for quantitative polymerase chain reaction (qPCR) impacts epidemiological insights during an mpox outbreak in Switzerland. 365 wastewater samples from three wastewater treatment plants in Switzerland from 9 March through 31 October 2022 were analyzed for mpox DNA using qPCR. We detected mpox DNA in 22% (79 of 365) wastewater samples based on a liberal definition of qPCR detection as any exponentially increasing fluorescence above the threshold. Based on a more restrictive definition as the lowest concentration at which there is 95% likelihood of detection, detection was 1% (5 of 365). The liberal definition shows high specificity (90%) and accuracy (78%), but moderate sensitivity (64%) when benchmarked against available clinical case reporting, which contrasts with higher specificity (98%) but lower sensitivity (10%) and accuracy (56%) of the 95% likelihood definition. Wastewater-based epidemiology applied to an emergent pathogen will require optimizing public health trade-offs between reporting data with high degrees of uncertainty and delaying communication and associated action. Information sharing with relevant public health stakeholders could couple early results with clear descriptions of uncertainty. Impact Statement: When a novel pathogen threatens to enter a community, wastewater-based epidemiology offers an opportunity to track its emergence and spread. However, rapid deployment of methods for to detect a novel pathogen may rely on assays with uncertain sensitivity and specificity. Benchmarking the detection of mpox DNA in Swiss wastewaters with reported clinical cases in 2022, we demonstrate how definitions of detection of a qPCR assay influence epidemiological insights from wastewater. The results highlight the need for information sharing between public health stakeholders that couple early insights from wastewater with descriptions of methodological uncertainty to optimize public health actions.