Robert Möller

Growing concerns regarding the spread of antibiotic resistance, together with increasing regulatory demands for advanced wastewater treatment, necessitate sensitive high-throughput analytical methods for monitoring antibiotic residues in the environment. In this study, an automated workflow for the determination of multi-class antibiotics in environmental waters was developed by combining a miniaturized 96-well solid-phase extraction (SPE) protocol with LC–HRMS detection. The SPE procedure enabled enrichment of 5 mL water samples to final extract volumes of 50 µL, corresponding to an enrichment factor of 100, while allowing direct injection of the SPE eluates into the LC–HRMS system without additional sample treatment. The automated workflow enabled parallel processing of up to 48 samples within 45 min while requiring less than 2 mL of organic solvent per sample. Comprehensive method validation demonstrated excellent analytical performance, including high linearity and method limits of quantification below 1 ng L-1 for all investigated antibiotics. Matrix effects, particularly in wastewater effluent, as well as variations in extraction recovery were effectively compensated using analyte-specific isotopically labeled internal standards. The applicability of the workflow for high-throughput environmental monitoring was demonstrated by analyzing wastewater effluent and river water samples, revealing the widespread occurrence of sulfamethoxazole, trimethoprim, ciprofloxacin, levofloxacin, azithromycin, clarithromycin, erythromycin, and roxithromycin, ranging from ultra-trace levels in river water to substantially elevated concentrations in wastewater effluent. Thus, the developed workflow represents a robust and sensitive high-throughput approach for the analysis of antibiotic residues in environmental waters.

Since the COVID-19 pandemic, wastewater monitoring has become an additional tool in the surveillance of infectious diseases. Many EU countries put wastewater surveillance systems (WSS) in place to track SARS-CoV-2 and its variants and other pathogens, such as the influenza virus or Respiratory syncytial virus (RSV). In Germany, several research and pilot projects funded by the EU, the Federal Ministry of Education and Research, the Federal Ministry of Health, and projects at Federal State level have been launched in the last four years. In Germany, wastewater monitoring was not implemented as a public health tool before the COVID-19 pandemic, but in September 2022, it has been legally determined in the German infection protection act (Infektionsschutzgesetz, IfSG). As Germany is a federal state, competencies in epidemic management partly belong to the 16 federal states (“Länder”). In the federal states, the local health authorities at the county (“Kreise”) level also have specific risk management and communication competencies. Furthermore, WSS has been incorporated into the revised Urban Wastewater Treatment Directive (EU) 2024/3019. For this reason, the federal states and local health authorities play a pivotal role in successfully implementing wastewater monitoring as a supplementary component of disease surveillance in Germany. Between November 2021 and August 2022, the federal state of Thuringia, Germany, supported a pilot study to implement a surveillance system for SARS-CoV-2-RNA in wastewater of 23 wastewater treatment plants in 17 counties in Thuringia. Here, we describe the study design and the system behind the logistics and the planning, and we provide an overview of the options for involving the public health service. Furthermore, the possibilities for IT concepts and approaches to innovative AI solutions are shown. We also aim to explore the feasibility and potential barriers to further implementing wastewater surveillance as a supplementary public health tool in Thuringia.

Wastewater monitoring for SARS-CoV-2 is a valuable tool for surveillance in public health. However, reliable analytical methods and appropriate approaches for the normalization of results are important requirements for implementing state-wide monitoring programs. In times of insufficient case reporting, the evaluation of wastewater data is challenging. Between December 2021 and July 2022, we analyzed 646 samples from 23 WWTPs in Thuringia, Germany. We investigated the performance of a direct capture-based method for RNA extraction (4S-method) and evaluated four normalization methods (NH₄-N, COD, N_tot, and PMMoV) in a pooled analysis using different epidemiological metrics. The performance requirements of the 4S method were well met. The method could be successfully applied to implement a state-wide wastewater monitoring program including a large number of medium and small wastewater treatment plants (<100,000 p.e) in high spatial density. Correlations between wastewater data and 7-day incidence or 7-day-hospitalization incidence were strong and independent from the normalization method. For the test positivity rate, PMMoV-normalized data showed a better correlation than data normalized with chemical markers. In times of low testing frequency and insufficient case reporting, 7-day-incidence data might become less reliable. Alternative epidemiological metrics like hospital admissions and test positivity data are increasingly important for evaluating wastewater monitoring data and normalization methods. Furthermore, future studies need to address the variance in biological replicates of wastewater.