Roger Dumke’s research while affiliated with Universitätsklinikum Carl Gustav Carus Dresden and other places

During the COVID-19 pandemic, wastewater-based epidemiology has been extensively used as a helpful tool for evaluation of the epidemic situation in catchments of wastewater treatment plants. In this context, knowledge about the rate of virus inactivation in wastewater is important for characterization of the influence of retention times in sewers on virus concentrations, of the storage periods before analysis in the laboratory, on virus elimination during treatment and for modeling approaches. In the present study, we genotyped SARS-CoV-2 in the respiratory tract specimens of infected patients and spiked the raw wastewater of five treatment plants with aliquots of these samples. The test preparations were incubated under practically relevant temperature conditions (14 °C) over 31 days. The linear decay rates resulted in comparable T90 values (30.5 d) for the Delta and the Omicron BA1 variants of SARS-CoV-2 without differences in using the E or S gene of the virus as the target for amplification. In contrast, the origin of wastewater influenced the inactivation rate of both variants significantly, with the mean T90 values varying between 24.3 and 53.1 days in the wastewater from the five plants. The data suggest that the inactivation rate of SARS-CoV-2 in wastewater is more strongly determined by the composition of the water than by the virus variant.

Vancomycin-resistant (VR) Enterococcus spp. can be detected in high concentrations in wastewaters and pose a risk to public health. During a one-year study (September 2022–August 2023), 24 h composite raw wastewater samples (n = 192) of a municipal wastewater treatment plant were investigated for cultivable enterococci. After growth on Slanetz–Bartley agar (SBA), a mean concentration of 29,736 ± 9919 cfu/mL was calculated. Using MALDI-TOF MS to characterize randomly picked colonies (n = 576), the most common species were found to be Enterococcus faecium (72.6%), E. hirae (13.7%), and E. faecalis (8.0%). Parallel incubation of wastewater samples on SBA and VRESelect agar resulted in a mean rate of VR enterococci of 2.0 ± 1.5%. All the tested strains grown on the VRESelect agar (n = 172) were E. faecium and carried the vanA (54.6%) or vanB gene (45.4%) with limited sequence differences. In susceptibility experiments, these isolates showed a high-level resistance to vancomycin (>256 µg/mL). Concentration of vancomycin was determined in 93.7% of 112 wastewater samples (mean: 123.1 ± 64.0 ng/L) and varied between below 100 ng/L (the detection limit) and 246.6 ng/L. A correlation between the concentration of vancomycin and the rate of VR strains among the total enterococci could not be found. The combination of incubation of samples on SBA and a commercial vancomycin-containing agar applied in clinical microbiology with a multiplex PCR for detection of van genes is an easy-to-use tool to quantify and characterize VR Enterococcus spp. in water samples.

Wastewater surveillance for SARS-CoV-2 has been demonstrated to be a valuable tool in monitoring community-level virus circulation and assessing new outbreaks. It may become a useful tool in the early detection and response to future pandemics, enabling public health authorities to implement timely interventions and mitigate the spread of infectious diseases with the fecal excretion of their agents. It also offers a chance for cost-effective surveillance. Reverse transcription-quantitative polymerase chain reaction (RTqPCR) is the most commonly used method for viral RNA detection in wastewater due to its sensitivity, reliability, and widespread availability. However, recent studies have indicated that reverse transcription droplet digital PCR (RTddPCR) has the potential to offer improved sensitivity and accuracy for quantifying SARS-CoV-2 RNA in wastewater samples. In this study, we compared the performance of RTqPCR and RTddPCR approaches for SARS-CoV-2 detection and quantification on wastewater samples collected during the third epidemic wave in Saxony, Germany, characterized by low-incidence infection periods. The determined limits of detection (LOD) and quantification (LOQ) were within the same order of magnitude, and no significant differences were observed between the PCR approaches with respect to the number of positive or quantifiable samples. Our results indicate that both RTqPCR and RTddPCR are highly sensitive methods for detecting SARS-CoV-2. Consequently, the actual gain in sensitivity associated with ddPCR lags behind theoretical expectations. Hence, the choice between the two PCR methods in further environmental surveillance programs is rather a matter of available resources and throughput requirements.

Fecal shedding of SARS-CoV-2 leads to a renaissance of wastewater-based epidemiology (WBE) as additional tool to follow epidemiological trends in the catchment of treatment plants. As alternative to the most commonly used composite samples in surveillance programs, passive sampling is increasingly studied. However, the many sorbent materials in different reports hamper the comparison of results and a standardization of the approach is necessary. Here, we compared different cost-effective sorption materials (cheesecloths, gauze swabs, electronegative filters, glass wool, and tampons) in torpedo-style housings with composite samples. Despite a remarkable variability of the concentration of SARS-CoV-2-specific gene copies, analysis of parallel-deposited passive samplers in the sewer demonstrated highest rate of positive samples and highest number of copies by using cheesecloths. Using this sorption material, monitoring of wastewater of three small catchments in the City of Dresden resulted in a rate of positive samples of 50% in comparison with composite samples (98%). During the investigation period, incidence of reported cases of SARS-CoV-2 in the catchments ranged between 16 and 170 per 100,000 persons and showed no correlation with the measured concentrations of E gene in wastewater. In contrast, constantly higher numbers of gene copies in passive vs. composite samples were found for human adenovirus and crAssphage indicating strong differences of efficacy of methods concerning the species investigated. Influenza virus A and B were sporadically detected allowing no comparison of results. The study contributes to the further understanding of possibilities and limits of passive sampling approaches in WBE.

Analysis of illicit drugs, medicines, and pathogens in wastewater is a powerful tool for epidemiological studies to monitor public health trends. The aims of this study were to (i) assess spatial and temporal trends of population-normalized mass loads of illicit drugs and nicotine in raw wastewater in the time of regulations against SARS-CoV-2 infections (2020–21) and (ii) find substances that are feasible markers for characterizing the occurrence of selected drugs in wastewater. Raw sewage 24-h composite samples were collected in catchment areas of 15 wastewater treatment plants (WWTPs) in urban, small-town, and rural areas in Germany during different lockdown phases from April 2020 to December 2021. Parent substances (amphetamine, methamphetamine, MDMA, carbamazepine, gabapentin, and metoprolol) and the metabolites of cocaine (benzoylecgonine) and nicotine (cotinine) were measured. The daily discharge of WWTP influents were used to calculate the daily load (mg/day) normalized by population equivalents (PE) in drained catchment areas (in mg/1,000 persons/day). A weekend trend for illicit drugs was visible with higher amounts on Saturdays and Sundays in larger WWTPs. An influence of the regulations to reduce SARS-CoV-2 infections such as contact bans and border closures on drug consumption has been proven in some cases and refuted in several. In addition, metoprolol and cotinine were found to be suitable as marker substances for the characterization of wastewater. A change in drug use was visible at the beginning of the SARS-CoV-2 crisis. Thereafter from mid-2020, no obvious effect was detected with regard to the regulations against SARS-CoV-2 infections on concentration of drugs in wastewater. Wastewater-based epidemiology is suitable for showing changes in drug consumption during the COVID-19 lockdown.

Purpose: Analysis of illicit drugs, medicines and pathogens in wastewater is a powerful tool for epidemiological studies to monitor public health trends. The aims of this study were to (i) assess spatial and temporal trends of population-normalized mass loads of illicit drugs and nicotine in raw wastewater in the time of regulations against SARS-CoV-2 infections (2020–21); (ii) find substances that are feasible markers for characterizing the occurrence of selected drugs in wastewater. Methods: Raw sewage 24-hour composite samples were collected in catchment areas of 15 wastewater treatment plants (WWTPs) in urban, small-town and rural areas in Germany during different lockdown phases from April 2020 to December 2021. Parent substances (amphetamine, methamphetamine, MDMA, carbamazepine, gabapentin and metoprolol) and the metabolites of cocaine (benzoylecgonine) and nicotine (cotinine) were measured. Results: The daily discharge of WWTP influents were used to calculate the daily load (mg/day) normalized by population equivalents (PE) in drained catchment areas (in mg/1,000 persons/day). An influence of the regulations to reduce SARS-CoV-2 infections such as contact bans and border closures on drug consumption has been proven in some cases and refuted in several. In addition, metoprolol and cotinine were found to be suitable as marker substances for the characterization of wastewater. A change in drug use was visible at the beginning of the Corona crisis. There after from mid-2020, no obvious effect was detected with regard to the regulations against SARS-CoV-2 infections on concentration of drugs in wastewater. Conclusions: Wastewater-based epidemiology is suitable for showing changes in drug use during the COVID-19 lockdown.

In the ongoing SARS-CoV-2 pandemic, there is a need for new strategies for surveillance and identification of arising infection waves. Reported cases of new infections based on individual testing are soon deemed inaccurate due to ever changing regulations and limited testing capacity. Wastewater based epidemiology is one promising solution that can be broadly applied with low efforts in comparison to current large-scale testing of individuals. Here, we are combining local wastewater data from the city of Dresden (Germany) along with reported cases and vaccination data from a central database (Robert-Koch-Institute) with virus variant information to investigate the correlation of virus concentrations in the wastewater and reported SARS-CoV-2 cases. In particular, we compared Linear Regression and Machine Learning (ML) models, which are both revealing an existing correlation of virus particles in wastewater and reported cases. Our findings demonstrate that the different virus variants of concern (Alpha, Delta, BA.1, and BA.2) contribute differently over time and parameters vary between variants, as well. By comparing the Linear Regression and ML-based models, we observed that ML can achieve a good fit for training data, but Linear Regression is a more robust tool, especially for new virus variants. We hereby conclude that deriving the rate of new infections from local wastewater by applying Linear Regression may be a robust approximation of tracing the state of the pandemic for practitioners and policy makers alike.

Dependent on the excretion pattern, wastewater monitoring of viruses can be a valuable approach to characterizing their circulation in the human population. Using polyethylene glycol precipitation and reverse transcription-quantitative PCR, the occurrence of RNA of SARS-CoV-2 and influenza viruses A/B in the raw wastewater of two treatment plants in Germany between January and May 2022 was investigated. Due to the relatively high incidence in both exposal areas (plant 1 and plant 2), SARS-CoV-2-specific RNA was determined in all 273 composite samples analyzed (concentration of E gene: 1.3 × 104 to 3.2 × 106 gc/L). Despite a nation-wide low number of confirmed infections, influenza virus A was demonstrated in 5.2% (concentration: 9.8 × 102 to 8.4 × 104 gc/L; plant 1) and in 41.6% (3.6 × 103 to 3.0 × 105 gc/L; plant 2) of samples. Influenza virus B was detected in 36.0% (7.2 × 102 to 8.5 × 106 gc/L; plant 1) and 57.7% (9.6 × 103 to 2.1 × 107 gc/L; plant 2) of wastewater samples. The results of the study demonstrate the frequent detection of two primary respiratory viruses in wastewater and offer the possibility to track the epidemiology of influenza by wastewater-based monitoring.