Inferring epidemic trajectories of viral infections from wastewater data can be a useful addition to clinical-based surveillance, as it provides low cost, population-level data that includes both symptomatic and asymptomatic individuals who contribute to the sewer system. However, methods for analyzing wastewater data have been primarily applied to high-resource settings. It remains an open question to what extent epidemic dynamics can also be estimated from wastewater data in low-resource settings, where measurements are less frequent and the underlying catchment population is not clearly characterized. We used SARS-CoV-2 wastewater data from the Gauteng Province in South Africa (June 2021 to March 2022). We used the R packages EpiSewer and EpiNow2 to estimate the effective reproduction number (Rt) from wastewater data and geographically matched clinical surveillance data, respectively. The comparison between wastewater and clinical Rt showed that the observed trends are not perfectly aligned. Despite these differences, wastewater and clinical Rt estimates identified similar transmission patterns, which were similar to the trend seen directly from the recorded data. Maximum wastewater Rt of 1.38 (95% CI: 1.17–1.44) was observed in early November 2021, whilst clinical Rt was 1.18 (90% CI: 0.85–1.27) in June 2021. The change in Rt aligned with an increase or decrease in recorded cases. Our findings demonstrate that, even with limited data, estimating epidemic trajectories is feasible, providing valuable insights for informing public health recommendations. However, whenever possible, we recommend using wastewater surveillance as a complementary tool for clinical surveillance.
Mthombothi et al. (2026) studied this question.