Circular Health
An approach that links observation, decision, intervention and renewed measurement in a verifiable cycle between environment and health.

Environmental surveillance
The systematic collection and interpretation of signals from wastewater, water or other matrices to support assessments of populations and territories, not individual diagnoses.

Distributed molecular testing
Decentralised analytical capacity located close to the sampling point or in local laboratories, within defined and controlled workflows.

Comparability between nodes
The ability to relate results produced in different places and at different times through consistent protocols, controls, units of measurement and metadata.

Escalation
A predefined pathway establishing when a signal requires new sampling, confirmation, further investigation or intervention.

Time from sampling to action
The operational interval encompassing collection, analysis, interpretation and decision-making; it is more informative than amplification time alone.

An environmental surveillance network does not become effective merely by producing results more quickly or closer to the sampling location. Value emerges when the signal remains interpretable throughout the chain: from collection to preparation, from controls to metadata, through to the criterion that triggers further investigation or intervention.

This is the operational scope within which Circular Health can become more than a conceptual framework. Distributed molecular testing can reduce distances and delays, but only within a system that keeps nodes comparable, integrates environmental data with other evidence and measures what happens after a decision. This article examines the conditions, limitations and metrics of this transition, while maintaining a clear boundary between environmental surveillance and individual diagnosis.

Water, soil, food, livestock, wildlife, cities and infrastructure continuously bring organisms, contaminants and populations into relation. One Health provides the institutional framework for understanding this interdependence. The 2022–2026 Joint Plan of Action by FAO, UNEP, WHO and WOAH links the health of humans, animals, plants and the environment and organises joint action across six tracks, including the integration of the environment [1].

Circular Health is a more recent and less established proposal. Mantegazza and colleagues formulated it in 2023 as a convergent approach to antimicrobial resistance through the Sustainable Development Goals roadmap [2]. In the same year, the Fraunhofer Group for Resource Technologies and Bioeconomy published a position paper bringing together One Health, health and circularity principles [3]. These are two conceptual perspectives, not a new global standard or evidence of operational effectiveness.

The most useful aspect of these proposals is the way they describe the process. A surveillance programme does not end with measurement: it interprets the signal alongside other evidence, determines whether to intervene and verifies what happens afterwards. The continuity of this feedback is what makes the process circular. If results and responsibility remain separate, the volume of data increases but response capacity does not necessarily improve; when the pathway is defined, even a targeted measurement can support a proportionate preventive decision.

Instrument size and amplification time describe only part of the system. Assessing the technology requires an understanding of which distance it reduces in the real process and whether the time gained extends through to interpretation and action.

In the centralised model, an environmental sample passes through storage, transport, accessioning, preparation, the analytical queue, verification and reporting. In an urgent investigation of water quality, the surveillance of a remote catchment or the coordinated monitoring of multiple sites, a substantial portion of the delay arises before and after the molecular reaction.

A distributed molecular testing network moves certain stages towards the collection site or decentralised laboratories. This can shorten the chain of custody and, during the same mission, allow sampling to be repeated, multiple points to be compared or further investigation to be initiated while the event is still under way. The local node expands the options for observation; the central laboratory remains essential for confirmation, characterisation, method development and control of comparability.

The available evidence shows concrete but circumscribed possibilities. Billington and colleagues compared a portable qPCR thermocycler with a benchtop instrument using known targets and freshwater samples: in the small set examined, the two systems showed similar repeatability and sensitivity [4]. The study concerns a single instrument and a limited experimental scope; it does not demonstrate the equivalence of an entire technology class.

Zan and colleagues brought filtration, extraction and qPCR into a mobile laboratory. A marker of faecal contamination was quantified within three hours of sampling; in the methodological comparison, results from the portable workflow agreed within ±0.3 log10 with those obtained using conventional equipment. The entire process required two experienced operators, and filtration, at approximately thirty minutes, remained the slowest stage [5]. The evidence supports the feasibility of that specific workflow, not the automatic transferability of every assay or matrix.

The two studies converge on an operational requirement: the local node must be assessed as a complete workflow, together with the instrument, protocol, sample, controls and expertise. If amplification capacity is distributed without the same quality safeguards, the result is a more fragmented network.

Environmental surveillance and individual diagnosis answer different questions. In the clinical setting, the sample and the question are associated with a person; wastewater, rivers and discharges instead represent populations, catchments or environments whose boundaries are often imperfect. The signal can vary with rainfall, flow rate, temperature, transit times, degradation, industrial activities, animal presence and collection methods.

WHO defines wastewater and environmental surveillance as surveillance based on population samples from wastewater or environmental waters affected by human activities. Its 2024 pilot guidance places it within multimodal surveillance [6]. In 2025, ECDC reiterated that wastewater data can contribute to risk assessment and public health decisions, provided they are interpreted and communicated alongside other surveillance sources [7].

A positive result indicates that the molecular target was detected within the scope of the method. On its own, it cannot identify who released it, determine the number of infected people, demonstrate viability or infectivity, or quantify health risk. Some targets may also have animal or environmental sources. Non-detection likewise requires caution: it may result from insufficient concentration, sampling frequency, recovery or sensitivity [6,7].

Between September and December 2024, vaccine-derived poliovirus type 2 was detected in wastewater in Finland, Germany, Poland, Spain and the United Kingdom without reported human cases. ECDC treated the signal as grounds for strengthening vigilance, vaccination coverage and surveillance [8]. The data were useful because they informed a risk assessment; they were not equivalent to a count of people who were ill.

In the following sections, ‘distributed diagnostics’ therefore describes decentralised molecular capacity serving environmental observation. Its output is surveillance information, not an individual clinical diagnosis. Maintaining this boundary protects scientific interpretation and prevents clinical claims that do not belong to environmental data from being transferred to them.

A portable thermocycler addresses only one part of the workflow. In environmental matrices, targets may be diluted, dispersed in large volumes or associated with particles, while humic acids, metals, detergents and other compounds can interfere with extraction and PCR. Filtration, concentration, recovery, storage and controls therefore matter as much as amplification.

Sun and colleagues developed a workflow for four drinking-water pathogens. In their study, insoluble particles reduced the quantification efficiency of Campylobacter jejuni to 30–60%; a specific filter treatment removed inhibition under the conditions assessed [9]. That treatment cannot be generalised to other matrices. The result nevertheless shows why a true negative must be distinguished from inefficient extraction or an inhibited reaction.

Sampling choices define what a measurement can represent. A grab sample and a composite sample cover different time windows; similarly, upstream and downstream points answer different questions. In a multi-site network, apparently small differences in collection can produce systematic differences in results. Location, time, matrix, volume, weather conditions, flow, storage and processing times must therefore be defined before analysis.

To verify that a change reflects the phenomenon being observed, the protocol must document process, recovery and inhibition controls, the limit of detection and, where relevant, the limit of quantification, together with replicates and validity criteria. Data quality depends on this chain of control, not on the geographical location of the node.

To compare results obtained in different places and at different times, every number must retain its context: site or catchment, sampling method, reagent lot, instrument, controls, curves, units of measurement, thresholds, timings and deviations. Without common metadata and criteria, faster availability does not transform an isolated signal into network data.

The 2025 ECDC framework identifies timely electronic access and data integration as conditions for consolidating European wastewater surveillance [7]. On the genomic side, WHO describes a promising field that is still limited by fragmented knowledge, limited standardisation and uncertainty about the use of results in public decision-making [10]. As analytical resolution increases, defining how results will be integrated and used becomes more urgent.

Digital platforms and remote management can support traceability, the application of predefined criteria, protocol updates and node monitoring. To do so, they must operate with defined roles and access, data integrity, audit trails, operational continuity and proportionate cybersecurity measures. Automation can flag anomalies and organise time series; signal interpretation and decision-making remain transparent and under human responsibility.

Directive (EU) 2024/3019 concerning urban wastewater treatment makes this transition particularly timely. The recast introduces regular surveillance of parameters relevant to public health in wastewater, includes monitoring of antimicrobial resistance and requires coordination between competent authorities [11]. Its operational significance extends beyond increasing the number of tests: institutions with different languages, data and responsibilities must share priorities, methods, information flows and escalation pathways.

The maturity of a network is evident in what happens after the signal. Who receives it? Which criterion triggers new sampling or confirmation? Which indicators are consulted? Who communicates the result, using what wording and at which territorial level? When is measurement repeated after the intervention? These questions assign responsibility and define the transition from evidence to action. This is where the Circular Health loop closes — or remains incomplete.

Proximity makes certain environmental benefits plausible: less sample transport, reduced need for refrigerated storage, compact instruments and more targeted interventions. They must, however, be verified across the complete pathway. A decentralised node requires equipment, energy, maintenance, controls, consumables, reagents, packaging and waste management; actual capacity utilisation and repeat testing can alter the balance.

Available assessments show how strongly the outcome depends on the boundaries of the comparison. Torres and colleagues applied life-cycle assessment to methods for detecting waterborne pathogens and observed that transport and electricity can substantially change the relative advantage of the alternatives [12]. An LCA of molecular testing for COVID-19 highlighted, in a specific Chinese scenario, the contribution of kit production, waste treatment and transport across the complete cycle [13]. The values cannot be transferred directly to a different environmental network; the methodological principle can.

A valid comparison places side by side two pathways capable of producing the same useful information, with equivalent quality and frequency. It must account for transport distance and temperature, the number of samples per session, repeat rate, instrument lifetime, energy consumption, single-use materials, waste and the need for confirmation. Sustainability, total cost and resilience can be assessed on the basis of these data.

Assessment also continues after the test. If an early signal does not meet defined responsibilities, resources or intervention criteria, it adds analytical consumption without demonstrating a reduction in exposure. When, instead, it informs a defined action and subsequent measurement verifies the effects, the service delivered by the system can be assessed alongside the impact of the individual device.

Distributed molecular testing can support Circular Health if it reduces a genuinely critical distance for the use case. This may be the time between sampling and result, the ability to cover previously excluded territories, repeat a collection or keep a multi-site network under observation. Each application requires a specific combination of nodes, frequency and analytical depth.

A mature network maintains a continuous pathway: a defined public question, representative sampling, a robust workflow, comparable results, integration with other evidence, an escalation criterion, responsibility for intervention and return measurement. The reference laboratory confirms and characterises; the distributed node can anticipate and guide observation, or make it more frequent. The outcome depends on the connection between these two roles.

Amplification time therefore covers only part of the process. The most useful metric runs from sampling to appropriate action: a one-hour reaction does not accelerate the system if the result remains without context or responsibility for two days. Local data that are verified, shared and interpreted within the same operational timeframe instead turn proximity into capability.

In operational terms, Circular Health describes this continuity between observation, decision and verification. Success is measured by the quality of the decision and the ability to verify its effects, not by the amount of data generated.

Placing an instrument near a river, wastewater treatment plant or production site shortens the physical distance; it is not enough to make the system circular. The signal must pass through a reliable chain of sampling, analysis and interpretation, reach those responsible for taking action and return to the system as a verifiable intervention.

Technology can shorten this pathway and broaden what a network can observe. The time gained, however, becomes usable knowledge only if the sample, controls, metadata and governance hold the process together. Sustainability must also be sought there: in the comparison of complete pathways and in the value of the decisions they enable, not merely in the presence of a local node.

The value of a territorial molecular network therefore lies in a clearer cycle between environment, evidence and response — one responsible enough to be verified.