Haeusser, S., Möller, R., Smarsly, K., Al-Hakim, Y., Kreuzinger, N., Pinnekamp, J., Pletz, M. W., Kluemper, C., & Beier, S. (2023). SARS-CoV-2 Wastewater Monitoring in Thuringia, Germany: Analytical Aspects and Normalization of Results. Water, 15(24), Article 4290. https://doi.org/10.3390/w15244290
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, Ntot, 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.
en
Forschungsschwerpunkte:
Sustainable Production and Technologies: 40% Efficient Utilisation of Material Resources: 20% Environmental Monitoring and Climate Adaptation: 40%