SARS-CoV-2 Wastewater Monitoring in Thuringia, Germany: Analytical Aspects and Normalization of Results

Author:

Haeusser Sarah12ORCID,Möller Robert3ORCID,Smarsly Kay4ORCID,Al-Hakim Yousuf4,Kreuzinger Norbert5,Pinnekamp Johannes6,Pletz Mathias W.7ORCID,Kluemper Claudia1,Beier Silvio2

Affiliation:

1. Department Hamm 2, Hamm-Lippstadt University of Applied Sciences, 59063 Hamm, Germany

2. Bauhaus-Institute for Infrastructure Solutions (b.is), Bauhaus University Weimar, 99423 Weimar, Germany

3. Analytik Jena GmbH + Co. KG, 07745 Jena, Germany

4. Institute of Digital and Autonomous Construction, Hamburg University of Technology, 21079 Hamburg, Germany

5. Institute for Water Quality and Resources Management, Vienna University of Technology, 1040 Vienna, Austria

6. Institute of Environmental Engineering, RWTH Aachen University, 52074 Aachen, Germany

7. Institute for Infectious Diseases and Infection Control, Jena University Hospital/Friedrich-Schiller-University, Am Klinikum 1, 07740 Jena, Germany

Abstract

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.

Funder

Bauhaus University Weimar, Germany

Thüringer Aufbaubank

Publisher

MDPI AG

Subject

Water Science and Technology,Aquatic Science,Geography, Planning and Development,Biochemistry

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