Regional and temporal differences in the relation between SARS-CoV-2biomarkers in wastewater and estimated infection prevalence-Insightsfrom long-term surveillance br

Wastewater-based epidemiology provides a conceptual framework for the evaluation of the prevalence of publichealth related biomarkers. In the context of the Coronavirus disease-2019, wastewater monitoring emerged as a com-plementary tool for epidemic management. In this study, we evaluated data from six wastewater treatment plants inthe region of Saxony, Germany. The study period lasted from February to December 2021 and covered the third andfourth regional epidemic waves. We collected 1065 daily composite samples and analyzed SARS-CoV-2 RNAconcentrations using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Regression modelsquantify the relation between RNA concentrations and disease prevalence. We demonstrated that the relation is siteand time specific. Median loads per diagnosed case differed by a factor of 3-4 among sites during both waves andwere on average 45 % higherduring the thirdwave. Inmost cases, log-log-transformed data achieved better regressionperformance than non-transformed data and local calibration outperformed global models for all sites. The inclusionof lag/lead time, discharge and detection probability improved model performance in all cases significantly, butthe importance of these components was also site and time specific. In all cases, models with lag/lead time and log-log-transformed data obtained satisfactory goodness-of-fit with adjusted coefficients of determination higher han 0.5. Back-estimation of testing efficiency from wastewater data confirmed state-wide prevalence estimation fromindividual testing statistics, but revealed pronounced differences throughout the epidemic waves and among thedifferent sites