Wastewater surveillance (WWS) of viruses can aid public health officials in monitoring community infection dynamics and act as an early warning system for the introduction of viral infectious diseases. In recent years, agile, low-cost devices called passive samplers have proven to be indispensable for targeted wastewater surveillance. However, the viral uptake kinetics are unexplored for most viruses, limiting the understanding of optimal deployment times and the representativeness of this sampling method for assessing community viral shedding. This study investigates the uptake kinetics of CrAssphage, Pepper Mild Mottle Virus, Human Adenovirus 40/41, Human Norovirus genogroup II, Enterovirus, and SARS-CoV-2 on electronegative membrane passive samplers. Viral uptake was modeled by linear and pseudo-first-order uptake models for up to 48 h (adjusted R²: 0.89–0.99), with minimal saturation for 48 h. Bench-scale experiments revealed enrichment of Human Adenoviruses 40/41 on membranes compared to all other viral targets for 24–48 h deployment (p < 0.05), while differences were less pronounced with shorter deployment durations. This work highlights virus-specific interactions with passive samplers and how deployment times can affect the relative concentrations of viruses detected. Understanding these kinetics is critical for selecting appropriate sampling strategies and normalization methodologies for WWS of viral infectious diseases.

Biofilm formation in drinking water distribution systems is primarily managed by disinfectants such as free chlorine (FC) and monochloramine (MC). However, there is limited understanding of their long-term and dynamic effects on biofilm development. To address this, a 56-week study was conducted to comprehensively assess biofilm development in terms of microbial quantity and community under different disinfection regimes: no chlorine (NC), FC (0.1 mg/L), and MC (0.4 mg/L). The results showed that both FC and MC significantly inhibited biofilm growth compared to the NC condition while shaping distinct biofilm communities. Notably, FC drastically reduced biofilm biomass and community diversity, resulting in a more uniform biofilm community predominantly composed of Proteobacteria (e.g., Rhizobacter spp., Pseudomonas spp., and Hyphomicrobium spp.), indicating stronger selection pressures on the microbial population. In contrast, though MC effectively reduced the biofilm biomass to a level comparable to that of FC, it maintained a high diversity comparable to that of NC (dominated by Sphingobium spp. and Nocardioides spp.), reflecting weaker selection pressure on bacterial community. Temporally, biofilm communities under all conditions started from nearly identical states. From week-19 and week-36 onwards, deterministic processes predominantly governed biofilm formation under FC and NC conditions, signifying that these biofilms reached a stable state. Differently, under MC condition, the community assembly was continually influenced by stochastic processes, with the biofilm not achieving stability until week-56. Overall, this study provides valuable insights into the long-term dynamics of biofilm development and evidenced that FC is better than MC in controlling biofilm formation, particularly from the community diversity perspective. This challenges classical views that MC is more effective than FC in penetrating and controlling biofilm, which may change the popularity of MC as a disinfectant in water utilities.

Classic faecal indicators, Escherichia coli and intestinal enterococci, were investigated as prospective proxies for presence of their resistant strains Extended Spectrum Betalactamase-producing (ESBL)-E. coli and Vancomycin Resistant Enterococci (VRE). These organisms are of global public health concern, and their tracing in water treatment systems is not yet standard practice. In this study, no significant difference was observed in the behaviour of the resistant bacteria and their sensitive counterparts during activated sludge treatment, chlorination, electrocoagulation and natural decay. Activated sludge treatment provided a 2.23 ± 0.13 log reduction value (LRV) for antibiotic resistant and sensitive bacteria alike. Disinfection by both free chlorine and electrocoagulation was slightly more effective against E. coli and ESBL-E. coli than against enterococci and VRE, though no significant difference was observed between the resistant bacteria and their sensitive counterparts. Decay experiments at 4, 13 and 24 °C showed a biphasic behaviour, with no relevant difference in decay between either of the indicators. It is therefore concluded that antibiotic-resistant ESBL-E. coli and VRE mirror the behaviour of faecal indicators E. coli and enterococci, experiencing the same rates of disinfection/decay, and maintaining similar ratios between sensitive and resistant populations before and after treatment.

The risk of infection by enteric pathogens in bathing waters is generally monitored by using fecal indicator bacteria (FIB). Mechanistic models are efficient tools to predict FIB concentrations in bathing waters, both in near-future forecasting and in long-term climate change projections. However, most existing mechanistic FIB models are limited by the availability of observations for validation and incorporation of all relevant physical, biological, and chemical (physico-biochemical) processes. Therefore, the quantitative influence of different physio-biochemical processes and impact factors is missing. To enhance the understanding of FIB fate in different aquatic systems, we developed a comprehensive yet generically applicable physico-biochemical model, focused on Escherichia coli (E. coli). It includes a die-off module and a sediment interaction module. Separate validation of the two sub-modules demonstrated the reliability of our modeling approach. The die-off module shows a higher R² value (0.88) and lower RMSE value (1.1 day^-1) than the existing models (0.48–0.79, and 1.8–7.2 day ^-1). This demonstrated an improvement by adding Ultraviolet-A and Ultraviolet-B (UVB) inactivation and UV spectrum extinction due to colored dissolved organic matter (CDOM) absorption. According to our sediment module validation, considering the impact of sediment composition on E. coli attachment can improve the allocation of E. coli between waters and sediments. Sensitivity analysis showed that 1) photo-inactivation is important in low CDOM waters, but not in high CDOM waters, where the UV penetration is limited; 2) the impact of sediment interaction can extend the duration of a peak event in high turbid waters. This work demonstrated the dominant impact factors in different aquatic systems for E. coli prediction. The new generic model enables better simulation of bathing water quality across different types of aquatic environments, which can be a useful tool to inform management at bathing sites. Future applications can choose processes selectively from the new FIB physico-biochemical model and couple it with appropriate hydrological/hydrodynamic models to address specific environmental conditions and research purposes.

This book addresses significant gaps in our understanding of how watershed microbial structures and functions respond to the pressures of urbanization. It consolidates rapidly evolving, yet often fragmented, global data on watershed microbiomes, providing critical insights into the impacts of urban pollution, human health risks, and long-term ecological consequences.Featuring the latest technological advancements in biological monitoring, microbial source-tracking technologies, and strategies for effective watershed management, this volume serves as a comprehensive and reliable source for the current state of urban watershed microbiology. It examines the unique challenges urbanization presents to ecosystems, especially in terms of atmospheric chemistry, hydrology, vegetation, and how these factors disrupt microbial communities that mediate essential ecosystem services like water purification, nutrient recycling, and degradation of pollutants.Together the two-volume work delves into the mechanisms behind the urban watershed syndrome—ecological degradation of streams—and explores many unanswered questions that hinder progress in understanding urban watershed microbiomes. With original research articles, reviews, and perspectives, this collection is a key resource for microbiologists, environmental scientists, engineers, and professionals involved in water quality, ecosystem management, and land-use planning. The hope is that this volume will inspire new breakthroughs, drive further research, and ultimately help shape effective strategies for addressing the ecological challenges of urban watersheds.

This book addresses significant gaps in our understanding of how watershed microbial structures and functions respond to the pressures of urbanization. It consolidates rapidly evolving, yet often fragmented, global data on watershed microbiomes, providing critical insights into the impacts of urban pollution, human health risks, and long-term ecological consequences.Featuring the latest technological advancements in biological monitoring, microbial source-tracking technologies, and strategies for effective watershed management, this volume serves as a comprehensive and reliable source for the current state of urban watershed microbiology. It examines the unique challenges urbanization presents to ecosystems, especially in terms of atmospheric chemistry, hydrology, vegetation, and how these factors disrupt microbial communities that mediate essential ecosystem services like water purification, nutrient recycling, and degradation of pollutants.Together this two-volume work delves into the mechanisms behind the urban watershed syndrome—ecological degradation of streams—and explores many unanswered questions that hinder progress in understanding urban watershed microbiomes. With original research articles, reviews, and perspectives, this collection is a key resource for microbiologists, environmental scientists, engineers, and professionals involved in water quality, ecosystem management, and land-use planning. The hope is that this volume will inspire new breakthroughs, drive further research, and ultimately help shape effective strategies for addressing the ecological challenges of urban watersheds.

Faecal contamination across the lettuce value chain was assessed in Maputo, Mozambique. Escherichia coli was used as an indicator of faecal contamination, with concentrations ranging from 3.4 to 5.7 log units/100 ml in groundwater, river water and partially treated wastewater. Municipal tap water used to wash lettuce heads in the markets had lower than 1 log unit/100 ml. Irrespective of the source of irrigation water, the lettuce heads were contaminated throughout the value chain, with concentrations ranging between 6.5 and 7.8 log units/100 g. Interventions and awareness raising should be applied at every stage of the value chain.

Although simulated studies have provided valuable knowledge regarding the communities of planktonic bacteria and biofilms, the lack of systematic field studies have hampered the understanding of microbiology in real-world service lines and premise plumbing. In this study, the bacterial communities of water and biofilm were explored, with a special focus on the lifetime development of biofilm communities and their key influencing factors. The 16S rRNA gene sequencing results showed that both the planktonic bacteria and biofilm were dominated by Proteobacteria. Among the 15,084 observed amplicon sequence variants (ASVs), the 33 core ASVs covered 72.8 %, while the 12 shared core ASVs accounted for 62.2 % of the total sequences. Remarkably, it was found that the species richness and diversity of biofilm communities correlated with pipe age. The relative abundance of ASV2 (f_Sphingomonadaceae) was lower for pipe ages 40–50 years (7.9 %) than for pipe ages 10–20 years (59.3 %), while the relative abundance of ASV10 (f_Hyphomonadaceae) was higher for pipe ages 40–50 years (19.5 %) than its presence at pipe ages 20–30 years (1.9 %). The community of the premise plumbing biofilm had significantly higher species richness and diversity than that of the service line, while the steel-plastics composite pipe interior lined with polyethylene (S-PE) harbored significantly more diverse biofilm than the galvanized steel pipes (S-Zn). Interestingly, S-PE was enriched with ASV27 (g_Mycobacterium), while S-Zn pipes were enriched with ASV13 (g_Pseudomonas). Moreover, the network analysis showed that five rare ASVs, not core ASVs, were keystone members in biofilm communities, indicating the importance of rare members in the function and stability of biofilm communities. This manuscript provides novel insights into real-world service lines and premise plumbing microbiology, regarding lifetime dynamics (pipe age 10–50 years), and the influences of pipe types (premise plumbing vs. service line) and pipe materials (S-Zn vs. S-PE).

Background
Wastewater surveillance may support early and comprehensive detection of infectious diseases’ community transmission, particularly in settings where other health surveillance systems provide biased or limited information. Amid the SARS-CoV-2 pandemic, deploying passive samplers to monitor targeted populations gained importance. Evaluation of the added public health value of this approach in the field can support its broader adoption.

Aim
We aimed to assess the feasibility and utility of on-demand wastewater surveillance, employing passive samplers, for SARS-CoV-2 and monkeypox virus (MPXV) in small/targeted populations, also considering ethical aspects.

Methods
Pilot case studies in the Rotterdam-Rijnmond region were used for a systematic assessment of the feasibility and utility of wastewater monitoring of SARS-CoV-2 (variants) and MPXV using passive sampling. Each case study was instigated by actual questions from the Public Health Service about disease transmission.

Results
Case study results demonstrated the feasibility and utility of on-demand wastewater surveillance with successful identification of a local peak in SARS-CoV-2 transmission, early detection of wider Omicron variant transmission after the first case was reported, as well as indication of no emerging local MPXV transmission. Ethical considerations led to the abandonment of one case study involving a displaced population.

Conclusions
The study confirms the feasibility and utility of passive sampling for real-time infectious disease surveillance, at desired spatiotemporal resolution. Ethical concerns and operational challenges were identified, highlighting the need for early stakeholder engagement and ethical guideline adherence. The method could be used to study under-surveyed populations and be extended beyond SARS-CoV-2 and MPXV to other pathogens.

Pathogen intrusion in drinking water systems can pose severe health risks. To better prepare in planning and responding to such events, computational models that capture the intrusion and health impact dynamics are needed. This study presents a novel benchmark testbed that integrates current knowledge on pathogen transport and fate in chlorinated systems and can assess infection risk from contamination events. The model considers organic matter degradation, chlorine decay mechanisms, pathogen inactivation kinetics, as well as stochastic water demands. We studied modeling of wastewater intrusion events that can occur anywhere within a chlorinated and non-chlorinated network. We applied the Quantitative Microbial Risk Assessment framework focusing on three pathogens: enterovirus, Campylobacter, and Cryptosporidium, and their respective dose-response models. Synthetic household-level water demand time series were used to model the individual water consumption timing and calculate the infection risk (exposure via ingestion). Model outcomes indicate that while chlorination aids mitigation, larger contaminations can still lead to infections due to chlorine resistance (for Cryptosporidium) and chlorine depletion at the contamination point. In our example scenarios, chlorine-susceptible pathogens infected 0.78–26.6% of the downstream population, while chlorine-resistant ones infected the entire downstream population. Enterovirus infection risk is higher, despite the concentrations in the contamination source being lower, due to the lower susceptibility to chlorine than Campylobacter. In non-chlorinated networks, the modeled wastewater contamination events led to 11–46% infection risk in the total population, depending on the contamination location. Hydraulic uncertainty had a limited influence on infection risk. Furthermore, Campylobacter's infection risk is more sensitive to the initial concentration in the contamination source whereas enterovirus infection risk to the inactivation rate. The model further indicates that the time window for effective mitigation of the magnitude of a waterborne outbreak is short (within hours).

Escherichia coli (E. coli) plays a central role as an indicator for fecal contamination to predict the possible presence of microbial pathogens in drinking water. Current detection methods for E. coli are based on time-consuming culture-based techniques. There is a strong need for methods to detect fecal contamination rapidly in distributed drinking water to prevent outbreaks of waterborne disease and support water utilities to efficiently manage their operations like actions to repair or maintain distribution pipes, to minimize impact on consumers. This study describes the validation and application of a qualitative real time reverse transcription PCR (RT-PCR) method targeting 16S ribosomal RNA (rRNA) for rapid detection of E. coli in distributed drinking water. The RT-PCR assay targets 16S rRNA, a highly abundant RNA in viable cells, enabling robust detection at the required sensitivity of 1 CFU/100 ml. The validation was performed by comparing the RT-PCR method with the culture-based chromogenic reference method (CCA) using the protocol and criteria described in ISO 16,140–2:2016. The validation demonstrated that this RT-PCR method can be used to specifically detect E. coli in a broad range of drinking water samples with at least the same limit of detection as the culture method (Relative Limit Of Detection = 0.75, range 0.43–1.43). The inclusivity study showed that the RT-PCR method was able to detect a broad range of E. coli strains derived from different sources and geographic areas, including pathogenic serotype O157 strains that are not detected with the culture method. The exclusivity study determined that other bacterial genera are not detected with this RT-PCR. However, Escherichia fergusonii was detected and, based on “in silico” analysis, it is expected that also E. albertii and E. marmotae and Shigella species will be detectable using this RT-PCR. An interlaboratory study confirmed that the RT-PCR and culture method have comparable sensitivities when tested by different participants at different laboratories. The application of RT-PCR to confirm the hygienic quality of distributed drinking water after actions to repair or maintain distribution pipes was compared with the culture method on 8076 routine samples, analyzed by the drinking water laboratories in the Netherlands. This comparison study showed a 96.4 % agreement between RT-PCR and culture. In 3.3 % of the samples E. coli was detected with RT-PCR and not with the culture method and in 0.1 % of the samples E. coli was only detected by culture confirming either a higher sensitivity for RT-PCR or the detection of RNA from uncultivable cells. Finally, the application of RT-PCR was highlighted during a contamination event in Belgium where we demonstrate the potency of RT-PCR as a tool to rapidly monitor the spread of microbial contamination and to monitor the effect of measures to remove the contamination This is the first fully validated rapid nucleic based method for detection of E. coli in distributed drinking water. These results demonstrate that this RT-PCR method can be used as a rapid alternative to the culture method to monitor E. coli in distributed drinking water. However, it should be emphasized that nucleic acid based detection methods rely on highly different detection principles (detection of captured nucleic acids present in a sample) than culture base methods (presence of cells cultivable on a selective medium) resulting in occasional different analysis results. Varying treatment and disinfection steps (UV, chlorine, monochloramine, Ozone) or environmental factors (decay) can influence the results and cause differences between RT-PCR and culture methods.

In a desktop exercise, a water utility’s emergency response to suspected wastewater contamination in a drinking water network was compared with a model-based approach using PathoINVEST. This tool simulates contamination scenarios and assists with locating the source of contamination using sampling results. The sampling procedure used a portable sensor that offers rapid (20 min time-to-result) screening of fecal contamination. Preliminary results show that the model-based approach is able to find the contamination source faster and with fewer samples than current practices. Integrating modeling and rapid sensor tools in emergency responses improves decision-making and public health protection in drinking water networks.

Short-term fecal pollution events are a major challenge for managing microbial safety at recreational waters. Long turn-over times of current laboratory methods for analyzing fecal indicator bacteria (FIB) delay water quality assessments. Data-driven models have been shown to be valuable approaches to enable fast water quality assessments. However, a major barrier towards the wider use of such models is the prevalent data scarcity at existing bathing waters, which questions the representativeness and thus usefulness of such datasets for model training. The present study explores the ability of five data-driven modelling approaches to predict short-term fecal pollution episodes at recreational bathing locations under data scarce situations and imbalanced datasets. The study explicitly focuses on the potential benefits of adopting an innovative modeling and risk-based assessment approach, based on state/cluster-based Bayesian updating of FIB distributions in relation to different hydrological states. The models are benchmarked against commonly applied supervised learning approaches, particularly linear regression, and random forests, as well as to a zero-model which closely resembles the current way of classifying bathing water quality in the European Union. For model-based clustering we apply a non-parametric Bayesian approach based on a Dirichlet Process Mixture Model. The study tests and demonstrates the proposed approaches at three river bathing locations in Germany, known to be influenced by short-term pollution events. At each river two modelling experiments (“longest dry period”, “sequential model training”) are performed to explore how the different modelling approaches react and adapt to scarce and uninformative training data, i.e., datasets that do not include event pollution information in terms of elevated FIB concentrations. We demonstrate that it is especially the proposed Bayesian approaches that are able to raise correct warnings in such situations (> 90 % true positive rate). The zero-model and random forest are shown to be unable to predict contamination episodes if pollution episodes are not present in the training data. Our research shows that the investigated Bayesian approaches reduce the risk of missed pollution events, thereby improving bathing water safety management. Additionally, the approaches provide a transparent solution for setting minimum data quality requirements under various conditions. The proposed approaches open the way for developing data-driven models for bathing water quality prediction against the reality that data scarcity is common problem at existing and prospective bathing waters.

The coronavirus disease 2019 pandemic highlighted the need for more rapid and routine application of modeling approaches such as quantitative microbial risk assessment (QMRA) for protecting public health. QMRA is a transdisciplinary science dedicated to understanding, predicting, and mitigating infectious disease risks. To better equip QMRA researchers to inform policy and public health management, an Advances in Research for QMRA workshop was held to synthesize a path forward for QMRA research. We summarize insights from 41 QMRA researchers and experts to clarify the role of QMRA in risk analysis by (1) identifying key research needs, (2) highlighting emerging applications of QMRA; and (3) describing data needs and key scientific efforts to improve the science of QMRA. Key identified research priorities included using molecular tools in QMRA, advancing dose–response methodology, addressing needed exposure assessments, harmonizing environmental monitoring for QMRA, unifying a divide between disease transmission and QMRA models, calibrating and/or validating QMRA models, modeling co-exposures and mixtures, and standardizing practices for incorporating variability and uncertainty throughout the source-to-outcome continuum. Cross-cutting needs identified were to: develop a community of research and practice, integrate QMRA with other scientific approaches, increase QMRA translation and impacts, build communication strategies, and encourage sustainable funding mechanisms. Ultimately, a vision for advancing the science of QMRA is outlined for informing national to global health assessments, controls, and policies.

Drinking water distribution systems are increasingly vulnerable to sewage intrusion due to aging water infrastructure and intensifying water stress. While the health risks associated with sewage intrusion have been extensively studied, little is known about the impacts of intruded bacteria and dissolved organic matter (DOM) on microbiology in drinking water. In this dynamic study, we demonstrate that the intrusion of 1 % sewage into tap water resulted in immediate contamination, including an 8-fold increase in biomass (TCC), a 48.9 % increase in bacterial species (ASVs), a 12.5 % increase in organic carbon content (DOC), and a 13.5 % increase in unique DOM molecular formulae. Over time, sewage intrusion altered tap water microbiology by accelerating bacterial growth rates (5-fold faster), selectively promoting ASVs in community succession, and producing 998 more unique DOM formulae. More significantly, statistical analysis revealed that the intrusion of 1 % sewage shifted the driving force of bacterial and DOM composition covariance from a DOM-dependent process in tap water to a bacterial-governed process post-intrusion. Our results clearly demonstrate the disruptive effects of sewage intrusion into tap water, emphasizing the urgent need to consider the long-lasting impacts of sewage intrusion in drinking water distribution systems, in addition to its immediate health risks.

Biofilm detachment contributes to water quality deterioration. However, the contributions of biofilm detachment from different pipes have not been quantified or compared. Following the introduction of partial reverse osmosis (RO) in drinking water production, this study analyzed particles at customers’ ends and tracked their origins to water distribution mains and service lines. For doing so, filter bags were installed in front of water meters to capture upstream detached particles, while biofilm from water main and service line were sampled by cutting pipe specimens. The results showed that elemental concentrations of the biofilm in mains were higher than those of service lines (54.3–268.5 vs. 27.1–44.4 μg/cm2), both dominated by Ca. Differently, filter bags were dominated by Fe/Mn (77.5–98.1%). After introducing RO, Ca significantly decreased in biofilms of mains but not service lines, but the released Fe/Mn rather than Ca arrived at customers’ ends. The ATP concentrations of service lines were higher than mains, which decreased on mains but increased in service lines after introducing RO. For the core ASVs, 13/24 were shared by service lines (17), mains (21), and filter bags (17), which were assigned mainly to Nitrospira spp., Methylomagnum spp., Methylocytis spp., and IheB2–23 spp. According to source tracking results, service lines contributed more than mains to the particulate material collected by filter bags (57.6 ± 13.2% vs. 13.0 ± 11.6%). To the best of our knowledge, the present study provides the first evidence of service lines’ direct and quantitative contributions to potential water quality deterioration at customers’ ends. This highlights the need for the appropriate management of long-neglected service line pipes, e.g., regarding material selection, length optimization, and proper regulation.

Agricultural aquifer storage recovery and transfer (ASTR) stores excess fresh water for later reuse in irrigation. Moreover, water quality improves because chemical pollutants and pathogens will be removed by degradation and attachment to the aquifer material. The source water may contain the bacterial plant pathogen Ralstonia solanacearum which causes plant infections and high yield losses. We used quantitative microbial risk assessment (QMRA) to investigate the removal of R. solanacearum during ASTR to predict infection risks of potato plants after irrigation with the recovered water. Laboratory experiments analyzed the ASTR treatment by investigating the bacterial die-off in the water phase and the removal by attachment to the aquifer sediment. Die-off in the water phase depends on the residence time and ranged between 1.3 and 2.7 log₁₀ after 10 or 60 days water storage, respectively. A subpopulation of the bacteria persisted for a prolonged time at low concentrations which may pose a risk if the water is recovered too early. However, the natural aquifer sand filtration proofed to be highly effective in removing R. solanacearum by attachment which depends on the distance between injection and abstraction well. The high removal by attachment alone (18 log₁₀ after 1 m) would reduce bacterial concentrations to negligible numbers. Upscaling to longer soil passages is discussed in the paper. Infection risks of potato plants were calculated using a dose-response model and ASTR treatment resulted in negligible infection risks of a single plant, but also when simulating the irrigation of a 5 ha potato field. This is the first QMRA that analyzed an agricultural ASTR and the fate of a plant pathogen focusing on plant health. QMRA is a useful (water) management tool to evaluate the treatment steps of water reclamation technologies with the aim to provide safe irrigation water and reduce risks disseminating plant diseases.

Despite high vaccination rates in the Netherlands, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to circulate. Longitudinal sewage surveillance was implemented along with the notification of cases as two parts of the surveillance pyramid to validate the use of sewage for surveillance, as an early warning tool, and to measure the effect of interventions. Sewage samples were collected from nine neighborhoods between September 2020 and November 2021. Comparative analysis and modeling were performed to understand the correlation between wastewater and case trends. Using high resolution sampling, normalization of wastewater SARS-CoV-2 concentrations, and ‘normalization’ of reported positive tests for testing delay and intensity, the incidence of reported positive tests could be modeled based on sewage data, and trends in both surveillance systems coincided. The high collinearity implied that high levels of viral shedding around the onset of disease largely determined SARS-CoV-2 levels in wastewater, and that the observed relationship was independent of variants of concern and vaccination levels. Sewage surveillance alongside a large-scale testing effort where 58 % of a municipality was tested, indicated a five-fold difference in the number of SARS-CoV-2-positive individuals and reported cases through standard testing. Where trends in reported positive cases were biased due to testing delay and testing behavior, wastewater surveillance can objectively display SARS-CoV-2 dynamics for both small and large locations and is sensitive enough to measure small variations in the number of infected individuals within or between neighborhoods. With the transition to a post-acute phase of the pandemic, sewage surveillance can help to keep track of re-emergence, but continued validation studies are needed to assess the predictive value of sewage surveillance with new variants. Our findings and model aid in interpreting SARS-CoV-2 surveillance data for public health decision-making and show its potential as one of the pillars of future surveillance of (re)emerging viruses.