Comparing wastewater-based and case-based R t estimates of SARS-CoV-2 transmission in Georgia using generalized linear mixed models

The COVID-19 pandemic has highlighted limitations in case-based surveillance due to inconsistent testing and reporting. Wastewater-based epidemiology (WBE) has emerged as a complementary surveillance approach for tracking SARS-CoV-2 transmission, capturing both symptomatic and asymptomatic infections. The aim of this study was to evaluate the effectiveness of WBE in estimating the effective reproduction number of SARS-CoV-2 in Georgia, USA. We used a Generalized Linear Mixed Model (GLMM) to analyse viral concentration data from multiple wastewater treatment plants (WWTPs) collected between 1 June 2022 and 15 December 2022. After controlling for flow rates and site-level heterogeneity, model residuals were transformed into a non-negative incidence-like series used to estimate wastewater-based. Wastewater-based was compared with case-based estimates using Spearman correlation. The two estimates showed concordant temporal patterns across most sites, with stronger correlations in areas with higher case counts (Spearman correlations ranging from 0.39 to 0.84, <![CDATA[ p). Wastewater-based tracked increases and decreases in transmission over similar time scales as case-based estimates, while exhibiting reduced sensitivity to short-Term changes in clinical testing and reporting behaviour. These findings suggest that WBE can support estimation of transmission trends and complement traditional case-based surveillance for public health monitoring.