Wastewater as a medium contains information on both circulating pathogens and drug consumption at the population level. This study combines tracking of respiratory viruses and quantification of pharmaceuticals as untargeted indicators of symptoms related to acute respiratory infections and influenza-like illnesses such as coughing, fever and pain. From January 2021 to June 2024, raw wastewater samples from ten locations covering 23% of the Swiss population were analysed. This encompassed 15 pharmaceuticals and four priority respiratory viruses including severe acute respiratory syndrome coronavirus virus-2 (SARS-CoV-2), respiratory syncytial virus (RSV), influenza A and influenza B viruses. The pharmaceutical compounds dextromethorphan, pheniramine, clarithromycin, acetaminophen and codeine showed a strong correlation with respiratory virus loads in wastewater. This enabled the estimation of pathogen-specific and cumulative symptom treatment in the population. In 2021 and 2024, notable increases in pharmaceutical loads without corresponding increases in viral loads signalled high community symptoms linked to unsurveilled pathogens. This study demonstrates that pharmaceutical surveillance can inform respiratory disease burden and highlights the value of integrated surveillance for assessing emerging public health threats beyond those routinely monitored.

Wastewater-based epidemiology is an established approach for monitoring population-level illicit drug use. Standard methods rely on 24-hour composite samples collected from treatment plant influent. While suitable for assessing long-term consumption patterns, composite samples obscure diurnal information on daily load dynamics - valuable for understanding substance sources and normalization strategies. Currently, the required, high manual effort limits the feasibility of diurnal monitoring applications.
In this study, we deployed a transportable, automated liquid chromatography-mass spectrometry system (MS²Field) at the influent of the wastewater treatment plant in Zurich, Switzerland (serving 471,000 people). Over an eight-week period from July to September 2023 - including school holidays and two major public events - samples were analyzed every 36 min (1909 total). Loads of five exogenous population biomarkers, six common illicit drug markers, and the cocaine adulterant levamisole were quantified. In parallel, hourly mobile phone data were used to estimate de facto population size and demographic composition in the catchment.
Automated analysis enabled the detection of consistent, weekday-specific intraday patterns for individual substances. Population biomarkers exhibited distinct temporal profiles: paraxanthine remained stable during working hours, while candesartan declined even at peak population times - highlighting implications for normalization, particularly with day visitors. Mobile phone-based occupancy data aligned with general trends but diverged during large events, likely due to mobile toilet use, whereas chemical markers directly reflected the contributing population.
During the special events, MDMA, ketamine, and amphetamine loads rose with distinct profiles - one event showing a gradual overnight rise, the other a morning peak. Daily MDMA loads were 20-fold higher during one event than typical weekends. Ketamine showed irregular spikes, possibly due to a smaller user base, rapid excretion, or direct input. Levamisole loads rose on weekends and during events, mirroring benzoylecgonine, indicating continued presence as harmful cocaine adulterant.
Automated analysis reveals short-term intraday trends, providing additional insights into the sources of chemical marker loads - such as consumption, excretion, and contributions from transient populations - that are typically averaged out in standard 24-hour composite samples.

Pollinosis is the most prevalent allergic disorder. Assessing the impact of real-world pollen exposure on symptoms remains challenging due to extensive patient-level efforts required.
This study explores the potential of wastewater-based epidemiology (WBE) to investigate the relationship between airborne pollen concentrations and antihistamine residues in wastewater as an indicator of pollinosis symptom treatment at the population-scale.
In Zurich (Switzerland), 279 wastewater samples were collected during 2021–2023. Each sample represents a 24-h period with excreta from approximately 471,000 individuals. Eleven antihistamine markers were analyzed in the samples using liquid chromatography high-resolution mass spectrometry. The relationship between antihistamine loads in wastewater and airborne pollen concentrations (47 taxa and miscellaneous pollen) was investigated by determining seasonal components of antihistamine loads and exploring pollen-specific contributions using Non-Negative Least Squares (NNLS) optimization.
Four antihistamines were detected in quantifiable amounts in wastewater. The first-generation antihistamine, diphenhydramine, demonstrated rather constant levels. In contrast, the three second-generation antihistamines - bilastine, cetirizine, and fexofenadine - showed pronounced day-to-day variation with strong correlations among each other. For fexofenadine, which was investigated in detail for its correlation with airborne pollen concentrations, approximately 50 % of the annual wastewater loads were associated with acute pollen exposure. Another 20 % related to baseline consumption during the pollen season, while the remaining 30 % seems unrelated to pollen. Birch, grasses, hazel, hornbeam, plane, and plantain explained most of the variance in wastewater loads (R² = 0.82), with grass pollen alone accounting for a quarter of the annual loads. Increased fexofenadine loads during periods without elevated concentrations of common allergenic pollen suggests the presence of additional triggers for allergy symptoms, potentially yew pollen.
Our study demonstrates that WBE can effectively reveal substantial day-to-day variation in antihistamine use related to pollen exposure. Thus, WBE presents an objective and questionnaire-independent method for investigating pollinosis symptom treatment at a population-scale.