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 ($ {R}_t $) 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 $ {R}_t $. Wastewater-based $ {R}_t $was compared with case-based $ {R}_t $estimates using Spearman correlation. The two $ {R}_t $ 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, $ p<0.001 $). Wastewater-based $ {R}_t $ 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.