The timing of this warning could hardly be more significant. Wastewater-based surveillance earned its reputation during the COVID-19 pandemic, when measurements of SARS-CoV-2 RNA in sewage proved to be a leading indicator of clinical case waves across cities and continents. That success spawned an entire discipline, and models such as the wastewater-based epidemic model developed for SARS-CoV-2 in three Canadian cities demonstrated that, under the right conditions, gene copy concentrations in influent sewage could be translated into estimates of infected individuals in a catchment. The European Union has since embedded wastewater surveillance into law through the recast Urban Wastewater Treatment Directive of 2024, and the European Centre for Disease Prevention and Control has published a framework for integrating wastewater data into infectious disease surveillance at the EU level. Antimicrobial resistance is now a priority target of these systems.

Yet the Cyprus-based authors argue that the epidemiological machinery that made viral surveillance interpretable does not yet exist for resistance. For viruses, researchers have invested heavily in quantifying shedding dynamics: how many genome copies an infected person excretes per gram of faeces, how those rates change over the course of infection, and how they differ between variants. Longitudinal studies of SARS-CoV-2, pepper mild mottle virus and crAssphage shedding, together with time-varying shedding models revisiting the 2013 poliovirus outbreak in Israel, have provided the conversion factors that turn a wastewater concentration into an approximate count of infected people. For antimicrobial resistance genes and resistant bacteria, no equivalent body of calibration data exists. The authors point out that faecal carriage of extended-spectrum beta-lactamase-producing Enterobacteriaceae in the general population, the duration of colonisation after international travel, and the effects of antibiotic exposure on the gut resistome are all documented in clinical studies, but these threads have never been woven into transfer functions that connect a gene abundance measured in sewage to a prevalence of carriage in the community above.

The technical reasons for this gap are formidable. A wastewater concentration is the product of a long and noisy chain of processes. It begins with the heterogeneous shedding of resistance determinants by carriers, which depends on the species of bacterium, the type of gene, whether the gene is carried on a chromosome or a plasmid, and whether it resides inside intact cells, in faecal particles, or as free extracellular DNA. It continues with in-sewer decay and partitioning, processes that have been characterised for pathogens such as Campylobacter jejuni and Campylobacter coli but that differ for every gene and microbe of interest. Hydraulic conditions, temperature, sewer biofilms and sediment resuspension all modulate what arrives at the sampling point. Sampling itself, whether flow-weighted composite or grab, introduces further uncertainty. By the time a sample reaches the laboratory, the signal is a composite whose relationship to the original biological state in the population is mediated by dozens of parameters, most of which are unknown for antimicrobial resistance.

Measurement technology compounds the problem. Quantitative metagenomics, which promises absolute quantification of resistance genes across thousands of loci simultaneously, is advancing quickly, and recent work has begun to establish detection limits for environmental monitoring of antibiotic resistance and for viruses. But the Cyprus team emphasises that analytical quantification is not the same as epidemiological calibration. A measurement can be perfectly reproducible and still be uninterpretable if nobody knows what concentration corresponds to what burden of carriage, what change in concentration corresponds to what change in incidence, or what effluent concentration corresponds to what environmental exposure risk. The authors describe this as quantifying variation without resolving biological states, a phrase that captures the epistemological core of their argument: surveillance data are being collected and compared, but the mapping from data to meaning remains undefined.

The downstream half of the problem, the effluent side, is equally under-calibrated. Wastewater treatment plants are known to substantially reduce the load of resistance genes and resistant bacteria leaving a catchment, with studies showing that extended-spectrum beta-lactamase and carbapenemase genes are substantially and sequentially reduced during conveyance and treatment of urban sewage. But removal efficiency varies enormously with treatment technology, capacity overloading, and the fate of intracellular versus extracellular DNA during processes such as ultrafiltration, ultraviolet disinfection and chlorination. Paradoxically, some disinfection steps may promote rather than reduce resistance spread: chlorine disinfection has been shown to facilitate natural transformation of bacteria through reactive oxygen species-mediated oxidative stress, and disinfection byproducts can increase transformation rates of environmental DNA in model organisms such as Acinetobacter baylyi. Without calibrated models of these processes, an effluent measurement cannot be translated into a statement about the resistance burden delivered to a receiving river, coastal water or irrigation system.

That environmental endpoint matters because the receiving environments are not passive sinks. Research along the wastewater-river continuum has documented the dissemination and persistence of antimicrobial resistance far downstream of discharge points. Treated wastewater irrigation has been shown to alter the resistance profiles of agricultural soils, subsoil pore-water and rhizospheres, while biofilms in reclaimed water distribution systems act as hot spots of horizontal gene transfer. Heavy metals such as copper accelerate the conjugative transfer of resistance genes in freshwater microcosms, and even herbicide selection can promote antibiotic resistance in soil microbiomes. Sludge and compost application to land introduces further pathways. Each of these environmental compartments hosts its own ecology of gene exchange, shaped by pH, soil type, moisture and microbial community composition. The authors argue that a calibrated surveillance framework must therefore serve two distinct interpretive goals simultaneously: translating influent signals into population-level epidemiological burden, and translating effluent signals into quantified risk of environmental introduction and subsequent exposure of humans, animals and crops.

The Perspective, illustrated with a conceptual overview of the calibration gap and a proposed calibration solution for interpreting epidemiological data and environmental introduction risk, does not merely diagnose the problem; it sketches what a solution would require. Drawing on the authors’ experience validating the national-scale SARS-CoV-2 surveillance system in Cyprus, and on emerging methods such as metagenomic absolute quantification with cellular internal standards and microbiome-based microbial risk assessment across multiple environments, they call for systematic studies that establish the missing transfer functions. These include quantifying shedding of resistance determinants by carriers in the community, characterising in-sewer and treatment-plant fate for priority genes and bacteria, and linking measured effluent concentrations to quantified exposure in receiving environments through models that account for dilution, decay, regrowth and gene transfer. Global comparative work, such as the exploration of human faecal and sewage resistomes as a function of socio-economic status, and metagenomic source attribution of resistance in wastewater, provides the kind of comparative baseline that calibration will ultimately require.

The stakes of getting this right are considerable. Antimicrobial resistance is one of the leading global threats to public health, and wastewater offers something clinical surveillance cannot: a continuous, catchment-wide, pathogen-agnostic signal that does not depend on patients seeking care or on laboratories reporting results. Wastewater surveillance has already revealed potential underreporting of disease cases in the Detroit area for Salmonella enterica, Campylobacter jejuni and norovirus, and has detected early introductions of the emerging fungal pathogen Candida auris in Utah. Small-scale wastewater-based epidemiology studies of antibiotic resistance are proliferating worldwide. But the Cyprus authors warn that without calibration, these signals risk being over-interpreted, with policy decisions made on the basis of numbers whose epidemiological and environmental meaning is unknown. Conversely, a properly calibrated system could convert routine sewage measurements into actionable estimates of community carriage prevalence and quantified environmental release, transforming wastewater plants from passive sentinels into genuine early-warning infrastructure.

The message of the Perspective is ultimately one of disciplined optimism. The raw ingredients for calibration already exist, scattered across clinical cohort studies of gut colonisation, environmental microbiology of sewers and treatment plants, and risk assessment frameworks developed for water reuse under EU Regulation 2020/741. What is missing is the deliberate, coordinated effort to assemble these ingredients into validated models, much as the viral surveillance community did in the years after 2020. The authors, writing with support from the SPORE-MED project under the PRIMA Programme and the EU-WISH joint action on integrated wastewater surveillance for public health, frame calibration not as an academic luxury but as the precondition for the next phase of the field. As regulators across Europe and beyond write antimicrobial resistance monitoring into wastewater law, the question they pose is blunt: a signal is only as valuable as the model that gives it meaning, and for antimicrobial resistance, that model has yet to be built.

Subject of Research: Calibration of wastewater-based antimicrobial resistance surveillance signals for epidemiological and environmental risk interpretation

Article Title: Calibrating antimicrobial resistance influent and effluent signals in wastewater systems

Article References: Naziri, Α., Chatzimichail, S., Karaolia, P., & Fatta-Kassinos, D. (2026). Calibrating antimicrobial resistance influent and effluent signals in wastewater systems. Nature Water. https://doi.org/10.1038/s44221-026-00701-1

Image Credits: AI Generated

DOI: 10.1038/s44221-026-00701-1

Keywords: antimicrobial resistance, wastewater surveillance, wastewater-based epidemiology, resistance genes, sewage, wastewater treatment plants, environmental risk, public health, metagenomics, horizontal gene transfer, effluent, Nature Water