Wastewater Surveillance for Public Health: From Sampling to Data Interpretation

Wastewater surveillance is the systematic collection and analysis of sewage to measure pathogens, chemicals, and other biomarkers that reflect the health status of the population contributing to a sewer catchment. This article provides a complete workflow for researchers, analysts, and public health officials who need to design, operate, and interpret wastewater surveillance programs. The practical outcome is a template for a wastewater surveillance protocol, including sampling schedules and data reporting forms, grounded in peer-reviewed evidence.

At a Glance

Wastewater-based epidemiology operates on a simple premise: people shed pathogens and chemical biomarkers into sewage, and measuring those signals at a treatment plant or upstream collection point reveals what is circulating in the community. The approach captures infections regardless of whether individuals seek clinical testing, which makes it valuable for detecting outbreaks, tracking trends, and identifying emerging variants.

The workflow described here follows four phases: defining the surveillance question, designing the sampling scheme, selecting and validating laboratory methods, and interpreting data for public health decisions. Each phase requires explicit documentation and quality controls.

Defining the Surveillance Objective

The first decision in any wastewater surveillance program is the question the program must answer. Different questions require different sampling designs, laboratory methods, and analytical approaches. A program designed to detect the early introduction of a novel pathogen needs different sensitivity than a program tracking trends in a well-established pathogen.

Surveillance Questions and Their Data Requirements

Public health actions that can be supported by wastewater surveillance include informing health authorities, identifying cases, detecting outbreaks, and evaluating intervention effectiveness. A scoping review of 974 wastewater surveillance studies found that only 84 described public health action, and only 28 of those incorporated strategies to facilitate action within their study designs. Studies conducted by public health institutes or targeting non-standard locations were more likely to result in action, while those with larger population sizes or focusing on residential areas were less likely to result in action. The most common public health actions included informing health authorities and identifying cases. This evidence suggests that programs designed with a clear action pathway are more likely to produce useful results than those designed purely for research purposes.

Matching Methods to Questions

The choice between quantitative PCR, targeted sequencing, and shotgun metagenomic sequencing depends on the surveillance objective. A study in western Germany collected composite influent wastewater samples over six weeks from a treatment plant serving a defined district and analyzed them using quantitative PCR and both targeted and shotgun metagenomic sequencing. All pathogens reported through routine public health surveillance during the study period were also detected in wastewater. In addition, wastewater surveillance identified signals from clinically relevant pathogens not captured by case-based surveillance. Sequencing approaches provided further resolution on pathogen diversity and resistance profiles. The combined use of targeted and untargeted methods revealed differences in sensitivity and resolution, with complementary strengths across approaches, and enabled the definition of a practical, tiered approach to support actionable surveillance at the regional level.

For programs with limited resources, a tiered approach is practical. Start with quantitative PCR for known targets, then add targeted sequencing when variant information is needed, and reserve shotgun metagenomics for exploratory surveillance or when novel pathogens are suspected.

Sampling Design and Site Selection

Sampling design determines the spatial and temporal resolution of the surveillance data. Poor sampling design cannot be corrected by sophisticated laboratory analysis or statistical modeling.

Catchment Characterization

The first step is to define the catchment area served by each sampling site. This includes the population size, the type of sewer system, the presence of industrial or commercial discharges, and the travel time from the most distant connection to the sampling point. The modifiable areal unit problem can affect spatial aggregation of wastewater surveillance data. A study of a New York State COVID-19 wastewater surveillance project examined the difference in wastewater SARS-CoV-2 concentrations between sampling at a city-level site and at upstream sampling sites, the correlation between wastewater data and clinical indicators at the wastewater treatment plant level and the more aggregated county level, and the proportion of population affected by misalignment of COVID-19 community risk levels at different spatial scales. The results showed that the modifiable areal unit problem can have a negative impact on risk perception by masking regions with high wastewater viral load or COVID-19 community risk level. On the other hand, the aggregation improved the correlation between wastewater surveillance and clinical measures by an average of 26.02 percent. This evidence indicates that the choice of reporting scale can either obscure or enhance the utility of wastewater data.

Sample Type and Collection Method

Composite samples collected over 24 hours are the standard for wastewater surveillance because they capture the diurnal variation in flow and pathogen shedding. Grab samples are less representative but may be acceptable for preliminary screening or when composite sampling is not feasible. The sampling schedule should account for the hydraulic retention time of the sewer system, which can range from hours to days depending on the network configuration.

Sample volume depends on the analytical method. Quantitative PCR typically requires smaller volumes than sequencing or chemical analysis. The sample container should be appropriate for the target analyte, and preservation methods must be validated for each target. A study of pharmaceutical biomarkers in wastewater tested analyte stability under variable storage conditions during sampling and long-term storage. High stability of most analytes was observed under tested storage conditions, with a few exceptions including diazepam, dihydroketoprofen, and 5-hydroxy-lansoprazole. This finding underscores the need to validate storage conditions for each target analyte instead of assuming universal stability.

Sampling Frequency

The sampling frequency should match the expected rate of change in the target signal and the speed of the public health decision that the data will inform. Weekly sampling is common for established pathogens, while daily sampling may be needed during outbreak response or when the surveillance question requires rapid detection. A study using wastewater sampling at wastewater treatment plants and university campuses in Monterrey and Mexico City between 2021 and 2022 trained simple clustering and regression based risk assessment models. When dividing weekly data points based on whether the seven day average daily new COVID-19 cases were above a certain threshold, the resulting clustering model could differentiate between weeks with surges in clinical reports and periods between them with an 87.9 percent accuracy rate. The clustering model provided satisfactory forecasts one week at 80.4 percent accuracy and two weeks at 81.8 percent accuracy. However, the prediction of the weekly average of new daily cases was limited, likely because of insufficient dimensionality in the database. This evidence suggests that simple models applied to weekly data can support outbreak detection, but quantitative prediction requires more data dimensions.

Laboratory Methods for Pathogen Detection

The laboratory workflow transforms raw wastewater into quantitative or sequence-based data. Each step, from concentration to nucleic acid extraction to detection, introduces variability that must be controlled and documented.

Virus Concentration and Nucleic Acid Extraction

Viruses in wastewater are present at low concentrations and must be concentrated before detection. The choice of concentration method affects recovery efficiency and downstream compatibility. A comparative evaluation of DNA extraction workflows for recovering the novel fecal marker pBI143 from wastewater compared polyethylene glycol precipitation and Nanotrap microbiome magnetic particle capture workflows using 12 wastewater samples collected across six treatment plants in Maryland. The Nanotrap workflow yielded significantly higher concentration of pBI143 compared to polyethylene glycol precipitation. The Nanotrap workflow used both magnetic nanoparticles A and B, instead of magnetic nanoparticle A alone, highlighting the necessity of optimization based on the intended targets for enhanced recovery. The extracted total nucleic acids by the Nanotrap workflow were further analyzed to quantify other fecal markers including crAssphage, tomato brown rugose fruit virus, and pepper mild mottle virus. No significant differences in the concentrations of pBI143, crAssphage, and tomato brown rugose fruit virus were observed, whereas the concentration of pepper mild mottle virus was significantly lower than that of the three fecal markers. Based on concentration alone, pBI143, tomato brown rugose fruit virus, and crAssphage were found to be better alternatives to pepper mild mottle virus as endogenous fecal markers.

Quantification Methods

Quantitative PCR and reverse transcription quantitative PCR are the most widely used methods for quantifying pathogen nucleic acids in wastewater. These methods require validated primers and probes, standard curves, and appropriate controls for inhibition and extraction efficiency. The limit of detection and limit of quantification must be established for each assay in the specific wastewater matrix being tested.

A study of pharmaceutical biomarkers in wastewater developed a solid-phase extraction ultra-performance liquid chromatography and tandem mass spectrometry method for 83 targets including 54 parent pharmaceuticals and 29 metabolites. Analyte recoveries varied between 75 percent and 125 percent for most analytes. Method detection limits ranged from 0.2 nanograms per liter to 5.6 nanograms per liter, while method quantification limits ranged from 0.2 nanograms per liter to 16.8 nanograms per liter. The overall average method accuracy and precision were 99.5 percent and 4.0 percent respectively. This level of analytical rigor is achievable for chemical targets and provides a model for the validation expectations of molecular methods.

Sequencing Methods

Sequencing adds a layer of information beyond quantification by revealing the genetic identity of pathogens in wastewater. Targeted amplicon sequencing focuses on specific genomic regions, while shotgun metagenomic sequencing captures all nucleic acids in the sample. A workflow integrating a high-purity laboratory procedure and an information theory based R package was validated using samples from a single urban node, successfully recovering known features of SARS-CoV-2 diversity at two contrasting stages of the COVID-19 pandemic. Clinically elusive mutations and single-nucleotide variants attributable to countrywide lineages were effectively identified in both early and late samples. The workflow also allowed detecting location-specific mutation frequency differences, revealing biogeographical trends that may escape clinical surveillance. Hotspots of high amino acid diversity were identified at receptor binding domain positions known to drive infectivity, transmissibility, and immune escape.

Nanopore sequencing offers a portable and cost-effective option for wastewater genomic surveillance. A study in Athens applied an upgraded Spike-Seq workflow integrating third-generation nanopore sequencing on the PromethION platform to achieve complete spike gene coverage from wastewater samples collected from December 2024 to February 2025. This workflow enabled simultaneous quantification of lineage-defining markers and detection of previously uncharacterized mutations in wastewater samples. The results identified the sustained dominance of the JN.1 lineage at greater than 80 percent frequency, with only transient signals from other variants. The study revealed recurrent substitutions in the N-terminal domain and S2 region, including L24F and I1130K, which indicate continued diversification of the dominant JN.1-associated viral population. Integration of sequencing with quantitative PCR viral load data revealed a peak in community infection pressure in January 2025, which decoupled from the rising frequency of specific mutational hotspots.

Addressing Viral Partitioning Behavior

The distribution of viruses between liquid and solid phases of wastewater affects both sampling strategy and data interpretation. A study demonstrated that pH and surfactants critically govern viral distribution between wastewater phases. Despite high solid-liquid partition coefficients, viruses predominantly reside in the liquid phase due to wastewaters low solid content. Leveraging these insights, the study conducted one-year reverse transcription quantitative PCR surveillance across a university and a city, capturing two SARS-CoV-2 waves and an influenza A outbreak. To address lineage demixing challenges from suboptimal sequencing, the researchers developed NextVpower, a deconvolution tool resolving co-circulating lineages while tracking critical mutations for clinical early-warning. NextVpower achieved the first demixing of both hemagglutinin and neuraminidase lineages for H3N2 influenza A virus in wastewater. This work advances the capacity to link wastewater-derived mutations to epidemiological trends.

Data Normalization and Quality Controls

Raw wastewater measurements must be normalized before they can be compared across sites or over time. Normalization accounts for variations in flow, population size, and fecal content.

Flow Normalization

Flow normalization converts concentration measurements to mass loads by multiplying the concentration by the flow rate at the time of sampling. This corrects for dilution from rainfall, groundwater infiltration, and industrial discharges. Mass loads are expressed as grams or copies per day and can be compared across sites with different flow characteristics.

Population and Fecal Normalization

Population normalization divides the mass load by the estimated population of the catchment. This allows comparison of per capita signals across sites. However, population estimates can be inaccurate, especially in catchments with significant commuter or tourist populations. Fecal normalization uses endogenous fecal markers to correct for variations in fecal input. A study comparing fecal markers found that pBI143, tomato brown rugose fruit virus, and crAssphage were better alternatives to pepper mild mottle virus as endogenous fecal markers based on concentration alone. The choice of normalization method should be documented and justified in the surveillance protocol.

Quality Controls and Inhibition Monitoring

Wastewater contains inhibitors that can interfere with nucleic acid amplification. Inhibition controls should be included in every assay run. These controls typically consist of a known quantity of an exogenous nucleic acid added to the sample before extraction, with the recovery rate calculated after amplification. Extraction efficiency controls measure the recovery of a known quantity of target nucleic acid added to a replicate sample. Both controls should be tracked over time to identify changes in matrix composition or laboratory performance.

Analytical Variability

The variability of wastewater measurements is substantial and must be quantified for each assay and matrix. A study of antibiotic-resistant bacteria in wastewater highlighted technical challenges associated with using wastewater to quantify temporal and spatial trends in antibiotic-resistant bacteria and antibiotic resistance genes. While antibiotic resistance genes and antibiotic-resistant bacteria are detectable in wastewater enabling early detection of novel resistance genes, quantitation of antibiotic-resistant bacteria and resistance genes with current methods is too variable to reliably track space and time variation. This evidence indicates that wastewater surveillance is better suited for detecting the presence of novel threats than for precisely quantifying trends in resistance.

Data Analysis and Interpretation

The analytical pipeline transforms normalized measurements into interpretable signals that can support public health decisions. This requires statistical methods appropriate for the data structure and the surveillance question.

Trend Analysis and Anomaly Detection

Time series analysis of wastewater concentrations can identify trends, seasonal patterns, and anomalies. Simple methods such as moving averages and control charts are often sufficient for detecting sustained changes in signal. More sophisticated methods, including clustering and regression models, can support risk classification and forecasting.

A study using wastewater data from Monterrey and Mexico City trained simple clustering and regression based risk assessment models to allow for informed prevention and control measures in high-affluence facilities, even when working with low-dimensionality datasets and a limited number of observations. The clustering model could differentiate between weeks with surges in clinical reports and periods between them with an 87.9 percent accuracy rate. The model provided satisfactory forecasts one week at 80.4 percent accuracy and two weeks at 81.8 percent accuracy. However, the prediction of the weekly average of new daily cases was limited, likely because of insufficient dimensionality in the database. This evidence suggests that simple models can support decision-making during epidemiological outbreaks, but regression algorithms for prediction using low-dimensionality datasets can still be improved.

Correlation with Clinical Surveillance

Wastewater data should be compared with clinical surveillance data to validate the wastewater signal and to identify discrepancies that may indicate gaps in clinical testing. A study of SARS-CoV-2 wastewater surveillance found that concentrations in wastewater correlate with trends in reported cases. However, the correlation can be affected by the modifiable areal unit problem, which can either mask or enhance the relationship depending on the spatial scale of aggregation.

Spatial Analysis and Geographic Information Systems

Spatial analysis and geographic information systems play a role in mapping the geographic distribution of viral loads, providing insights into the dynamics of virus transmission within communities. The integration of geographic information systems in wastewater surveillance enhances sampling site selection and ensures equitable monitoring across diverse populations. The innovative combination of geographic information systems with remote sensing data and predictive modeling offers a multi-faceted approach to understand virus spread. Challenges such as data quality, privacy concerns, and the necessity for interdisciplinary collaboration must be addressed.

Machine Learning Applications

Machine learning methods can support the interpretation of wastewater surveillance data, particularly for risk classification and forecasting. A study using wastewater data from Mexico trained clustering and regression models that could differentiate between weeks with surges in clinical reports and periods between them with high accuracy. The models provided satisfactory forecasts one and two weeks into the future. However, the prediction of the weekly average of new daily cases was limited, likely because of insufficient dimensionality in the database. This evidence indicates that machine learning can support decision-making but should be validated on local data before deployment.

Expanding Beyond Pathogens

Wastewater surveillance is not limited to infectious pathogens. The same infrastructure can measure chemicals, pharmaceuticals, and other biomarkers that reflect community health.

Pharmaceutical and Chemical Surveillance

Wastewater-based epidemiology can estimate community-wide non-communicable disease prevalence using pharmaceutical proxy data. A study introduced a workflow for estimation of non-communicable diseases prevalence by using pharmaceuticals and their metabolites as proxies. The study selected 83 targets including 54 parent pharmaceuticals and 29 metabolites. Three critical aspects were tested: solid-phase extraction ultra-performance liquid chromatography and tandem mass spectrometry method performance, biomarker stability under variable storage conditions, and accounting for human metabolism in back-calculations. The fully validated method was tested using community wastewater in the Southwest of England to estimate pharmaceutical usage, test metabolism correction factors, and compare results with prescription data. The new method for non-communicable disease approximation allowed for the estimation of the daily usage and intake of 69 targets with a standardized approach and a consistent reporting format.

Substance Use Monitoring

Wastewater-based epidemiology has emerged as a tool for monitoring community-level drug use, offering near real-time estimates and the potential to serve as an early warning system. A study presented a standardized, practical workflow for multi-drug detection in wastewater, aiming to minimize analyte loss and improve reproducibility. Composite samples were collected from multiple United States cities, transported on ice, and extracted using solid-phase extraction. Extraction efficiencies were compared using Oasis Hydrophilic-Lipophilic-Balanced and Mixed-mode Cation-Exchange cartridges, with the Mixed-mode Cation-Exchange sorbent providing complementary reversed-phase and cation-exchange interactions that enabled the retention of chemically diverse compounds across multiple drug classes. Analysis was performed with an ultra-high-performance liquid chromatography system coupled to a triple quadrupole mass spectrometer. Challenges such as analyte degradation, wastewater variability, and matrix effects can affect data quality and comparability across regions.

Environmental Chemical Surveillance

Liquid chromatography-high resolution mass spectrometry based suspect screening can expand semi-quantitative coverage in wastewater-based epidemiology. A study developed an integrated analytical workflow that expanded the coverage of environmental chemicals and enabled standard-free semi-quantitative analysis. Influent wastewater samples from nine wastewater treatment plants in Taiwan were re-examined using a single additional liquid chromatography-high resolution mass spectrometry analysis in full-scan and data-dependent acquisition modes. A total of 189 environmental compound signals were structurally identified, representing 79 unique chemical structures. Semi-quantitative concentration estimation was achieved using a single-point calibration strategy based on isotope-labeled internal standards originally included for illicit drug analysis, combined with ionization efficiency prediction tools. Internal cross-validation yielded median prediction errors of 2.3-fold in positive ionization mode and 5.0-fold in negative ionization mode. Population-normalized mass load analysis revealed regional differences in chemical exposure profiles, with elevated mass loads of smoking-related biomarkers.

Ethics, Privacy, and Governance

Wastewater surveillance raises ethical and legal questions that must be addressed in the program design. The primary concern is group privacy, because wastewater samples contain genetic material from all individuals contributing to the catchment.

Group Privacy and Legal Obligations

Existing scholarship has focused on using ethics or human rights based frameworks as a means of balancing the public health objectives of wastewater surveillance and the potential risks it might pose to group privacy. However, such frameworks greatly lack enforceability. A paper proposed the idea of the obligation as an alternative way to regulate wastewater surveillance systems. The legal codification of said obligations provides a method of ensuring that wastewater surveillance systems can be deployed effectively and equitably. The paper proposed that legal obligations for wastewater surveillance can be created and enforced through transparent and purposeful legislation, which would include limits on power and grant institutions substantial oversight, as well as paying heed to non-legislative legal means of enforcement, such as through courts or contracts. Introducing legal obligations for wastewater surveillance could therefore be highly useful to researchers, policymakers, corporate technologists, and government agencies working in this field.

Ethics Considerations for Monitoring

Establishing ethics considerations for monitoring is a key use case for wastewater surveillance. The measurements must translate into useful public health tools, which requires bridging the communication and knowledge gaps between researchers and public health responders. Key uses, barriers, and applicability of wastewater surveillance for supporting public health decisions and actions include establishing ethics consideration for monitoring.

Data Sharing and Genomic Data Policy

Wastewater genomic data may be subject to data sharing policies. The National Institutes of Health Genomic Data Sharing Policy provides expectations for the sharing of genomic data generated with NIH funding. Researchers should review applicable policies before depositing wastewater sequence data in public repositories. The NCBI Data Resources provide access to sequence data and associated metadata, while the EMBL-EBI Training program offers educational resources for researchers working with genomic data.

Data Management and Reporting

The value of wastewater surveillance depends on the quality and accessibility of the data. Data management practices should be established before sampling begins.

FAIR Data Principles

Wastewater surveillance data should be managed according to the FAIR Guiding Principles, which require that data be findable, accessible, interoperable, and reusable. The FAIR Guiding Principles were published in Scientific Data and provide a framework for data management that supports reproducibility and secondary use. Applying these principles to wastewater surveillance data requires documentation of sampling methods, laboratory protocols, quality controls, and data processing steps.

Data Reporting Forms

A standardized data reporting form should capture the following fields for each sample:

International Collaboration and Databases

International cooperation and wastewater surveillance databases can support public health decision-making. The rapid development of an international co-operation and wastewater surveillance database during the SARS-CoV-2 pandemic demonstrated the value of shared data infrastructure. Researchers should contribute to established databases where possible and document their data in a format that supports aggregation across sites and studies.

Common Failure Patterns

Wastewater surveillance programs can fail in predictable ways. Recognizing these patterns allows programs to correct course before data quality degrades.

Sampling Failures

The most common sampling failures include collecting grab samples when composite samples are needed, sampling at times that do not capture peak flow, using containers that adsorb or degrade the target analyte, and failing to maintain the cold chain during transport. Each of these failures introduces bias that cannot be corrected in the laboratory or during analysis.

Laboratory Failures

Laboratory failures include inadequate inhibition controls, unvalidated extraction methods, and failure to establish limits of detection and quantification in the specific wastewater matrix. A study of antibiotic-resistant bacteria in wastewater highlighted that quantitation of antibiotic-resistant bacteria and resistance genes with current methods is too variable to reliably track space and time variation. Programs that do not quantify this variability may overinterpret small changes in concentration.

Interpretation Failures

Interpretation failures occur when data are analyzed without accounting for the modifiable areal unit problem, when trends are assessed without appropriate statistical methods, or when wastewater data are compared with clinical data without acknowledging the differences in catchment and reporting scale. A study of the modifiable areal unit problem showed that aggregation can mask regions with high wastewater viral load or COVID-19 community risk level, while also improving the correlation between wastewater surveillance and clinical measures. Programs should report data at multiple spatial scales when possible and document the scale used for each decision.

Communication Failures

Communication failures occur when wastewater data are presented to public health officials or the public without adequate context. The measurements must translate into useful public health tools, which requires bridging the communication and knowledge gaps between researchers and public health responders. Programs should develop communication templates that explain the meaning of wastewater signals, the limitations of the data, and the actions that are appropriate at different signal levels.

Limitations and Escalation Criteria

Wastewater surveillance has inherent limitations that must be acknowledged in program design and reporting.

Sensitivity and Specificity Limitations

The sensitivity of wastewater surveillance depends on the population size, the shedding rate of the target pathogen, the recovery efficiency of the concentration method, and the analytical sensitivity of the detection method. A study in Lagos, Nigeria evaluated the prevalence of clinically relevant infectious pathogens in wastewater canals in 20 Local Government Areas. SARS-CoV-2 was not detected from wastewater in this study, despite the virus being present in the community. This finding illustrates that a negative wastewater result does not confirm the absence of infection in the catchment.

Quantitative Limitations

The quantitative accuracy of wastewater surveillance is limited by variability in flow, population, fecal content, and analytical recovery. A study of antibiotic-resistant bacteria found that quantitation of antibiotic-resistant bacteria and resistance genes with current methods is too variable to reliably track space and time variation. Programs should focus on qualitative detection and trend analysis instead of precise quantification.

Escalation Criteria

Professional escalation criteria should be defined in the surveillance protocol before data collection begins. The following criteria are appropriate for most programs:

The specific thresholds should be established based on local data and the surveillance objective. A study of wastewater surveillance in smaller college communities demonstrated that local universities can leverage scientific resources to advance public health equity in rural areas and enhance their community involvement. This cost-effective approach is especially well suited to rural areas where limited access to testing may worsen the spread of COVID-19 and quickly exhaust the capacity of local healthcare systems.

Frequently Asked Questions

What is the difference between wastewater surveillance and wastewater-based epidemiology?

Wastewater surveillance refers to the systematic collection and analysis of wastewater samples to detect and quantify pathogens, chemicals, or other biomarkers. Wastewater-based epidemiology is the broader field that interprets these measurements to estimate community health conditions, including infectious disease prevalence, non-communicable disease burden, and substance use patterns. Surveillance is the data collection component, while epidemiology encompasses the interpretation and public health application of that data.

How often should wastewater samples be collected?

The sampling frequency should match the expected rate of change in the target signal and the speed of the public health decision that the data will inform. Weekly sampling is common for established pathogens, while daily sampling may be needed during outbreak response. A study using weekly wastewater data from Mexico demonstrated that clustering models could differentiate between weeks with surges in clinical reports and periods between them with 87.9 percent accuracy, suggesting that weekly sampling can support outbreak detection.

What is the modifiable areal unit problem in wastewater surveillance?

The modifiable areal unit problem is a type of statistical bias that occurs when spatial data are aggregated into different areal units. In wastewater surveillance, this affects the choice of reporting scale, such as wastewater treatment plant level versus county level. A study in New York State found that aggregation can mask regions with high wastewater viral load or COVID-19 community risk level, while also improving the correlation between wastewater surveillance and clinical measures by an average of 26.02 percent. Programs should report data at multiple spatial scales when possible.

Can wastewater surveillance detect antibiotic-resistant bacteria?

Wastewater surveillance can detect antibiotic-resistant bacteria and antibiotic resistance genes, enabling early detection of novel resistance threats. However, a study found that quantitation of antibiotic-resistant bacteria and resistance genes with current methods is too variable to reliably track space and time variation. Wastewater surveillance is better suited for detecting the presence of novel resistance threats than for precisely quantifying trends in resistance.

What are the ethical considerations for wastewater surveillance?

The primary ethical concern is group privacy, because wastewater samples contain genetic material from all individuals contributing to the catchment. A paper in Water Research proposed the idea of the obligation as an alternative way to regulate wastewater surveillance systems, with legal codification providing a method of ensuring that wastewater surveillance systems can be deployed effectively and equitably. Programs should establish ethics considerations for monitoring before data collection begins.

How does wastewater surveillance compare with clinical surveillance?

Wastewater surveillance captures infections regardless of whether individuals seek clinical testing, which makes it valuable for detecting outbreaks and tracking trends in populations with limited testing access. A study in western Germany found that all pathogens reported through routine public health surveillance during the study period were also detected in wastewater, and wastewater surveillance identified signals from clinically relevant pathogens not captured by case-based surveillance. However, wastewater data cannot provide individual-level information and must be interpreted at the population level.

What methods are used to detect pathogens in wastewater?

Quantitative PCR and reverse transcription quantitative PCR are the most widely used methods for quantifying pathogen nucleic acids in wastewater. Targeted amplicon sequencing focuses on specific genomic regions, while shotgun metagenomic sequencing captures all nucleic acids in the sample. Nanopore sequencing offers a portable and cost-effective option for genomic surveillance. A study in Athens used nanopore sequencing to achieve complete spike gene coverage from wastewater samples and identified the sustained dominance of the JN.1 lineage at greater than 80 percent frequency.

How should wastewater surveillance data be reported to public health officials?

Wastewater surveillance data should be reported with clear context about the catchment, sampling methods, laboratory methods, quality controls, and limitations. A standardized data reporting form should capture sample identifiers, collection dates and times, site identifiers, catchment populations, flow rates, sample volumes, concentrations, mass loads, normalization methods, and quality control results. The measurements must translate into useful public health tools, which requires bridging the communication and knowledge gaps between researchers and public health responders.

Related Bioinformatics Guides

• Alternative Splicing Analysis from RNA-Seq Data
• Codon Usage Bias Analysis for Recombinant Vaccine Design
• The World Health Organization (WHO) and Global Genomic Surveillance
• Epigenetics and Computational DNA Methylation Analysis: Mechanisms, Methods, and Veterinary Applications
• Structural and Evolutionary Analysis of Rabies Virus Glycoprotein: Implications for Vaccine Design

References and Further Reading

• EMBL-EBI Training. European Bioinformatics Institute.
• NCBI Data Resources. National Center for Biotechnology Information.
• Genomic Data Sharing Policy. National Institutes of Health.
• The FAIR Guiding Principles. Scientific Data.
• SARS-CoV-2 Wastewater Surveillance for Public Health Action.. Emerging infectious diseases, 2021.
• Surveillance of public health pathogens in Lagos wastewater canals: a cross-sectional study.. BMC public health, 2024.
• Wastewater surveillance studies on pathogens and their use in public health decision-making: a scoping review.. The Science of the total environment, 2025.
• Advancing Public Health Surveillance: Integrating Modeling and GIS in the Wastewater-Based Epidemiology of Viruses, a Narrative Review.. Pathogens (Basel, Switzerland), 2024.
• Wastewater surveillance in smaller college communities may aid future public health initiatives.. PloS one, 2022.
• Wastewater surveillance of antibiotic-resistant bacteria for public health action: potential and challenges.. American journal of epidemiology, 2025.
• Balancing public health and group privacy: Ethics, rights, and obligations for wastewater surveillance systems.. Water research, 2024.
• Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review.. JMIR public health and surveillance, 2024.
• A new Wastewater-Based Epidemiology workflow to estimate community wide non-communicable disease prevalence using pharmaceutical proxy data.. 2024.
• Genomic surveillance of SARS-CoV-2: a resource-efficient wastewater-based workflow.. 2026.
• Wastewater genomic surveillance of SARS-CoV-2 by nanopore sequencing uncovers JN.1 prevalence and novel spike mutational hotspots in Athens during winter 2024-2025.. 2026.
• Wastewater-based epidemiology for public health - benefits and trade-offs of different molecular methods for the generation of actionable data in a small-town context.. 2026.
• Integrating liquid chromatography-high resolution mass spectrometry based suspect screening with ionization efficiency prediction to expand semi-quantitative coverage in wastewater-based epidemiology: application to environmental chemicals.. 2026.
• Comparative Evaluation of DNA Extraction Workflows for Efficient Recovery of pBI143 from Wastewater.. 2026.
• A Practical Framework for Wastewater-Based Monitoring of Substance Use in Public Health Settings.. 2026.
• Wastewater surveillance for SARS-CoV-2 to support return to campus: Methodological considerations and data interpretation. Current Opinion in Environmental Science & Health, 2022.
• The effect of the modifiable areal unit problem (MAUP) on spatial aggregation of COVID-19 wastewater surveillance data.. Science of the Total Environment, 2024.
• Interpretation of COVID-19 Epidemiological Trends in Mexico Through Wastewater Surveillance Using Simple Machine Learning Algorithms for Rapid Decision-Making. Viruses, 2025.
• Analysis insights to support the use of wastewater and environmental surveillance data for infectious diseases and pandemic preparedness.. Epidemics, 2025.
• Enhanced wastewater surveillance of respiratory viruses: Unraveling partitioning behavior and demixing co-circulating lineages.. Environment International, 2025.
• Making Waves: Collaboration in the time of SARS-CoV-2 - rapid development of an international co-operation and wastewater surveillance database to support public health decision-making. Water Research, 2021.
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• Tracking Mpox through wastewater: advances in environmental surveillance and analytical methodologies. Methods in Microbiology, 2026.
• Wastewater Surveillance Program Management and Execution: Lessons Learned from the COVID-19 Pandemic. 95th Water Environment Federation Technical Exhibition and Conference Weftec 2022, 2022.
• A systematic review on the incidence of influenza viruses in wastewater matrices: Implications for public health. Plos One, 2024.
• Wastewater-based epidemiology: A Brazilian SARS-COV-2 surveillance experience. Journal of Environmental Chemical Engineering, 2022.

This article is educational and does not replace validated analysis plans, institutional policy, clinical interpretation, or specialist review.