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SARS-CoV-2 wastewater monitoring in Thuringia, Germany : analytical aspects and normalization of results
Citation Link: https://doi.org/10.15480/882.8982
Publikationstyp
Journal Article
Date Issued
2023-12-15
Sprache
English
TORE-DOI
Journal
Citation
Water 15 (24): 4290 (2023-12-15)
Publisher DOI
Scopus ID
Publisher
Multidisciplinary Digital Publishing Institute
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.
Subjects
COVID-19
normalization
SARS-CoV-2
wastewater-based epidemiology
DDC Class
624: Civil Engineering, Environmental Engineering
Publication version
publishedVersion
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Name
water-15-04290.pdf
Type
Main Article
Size
6.14 MB
Format
Adobe PDF