Real-time county-aggregated wastewater-based estimates for SARS-CoV-2 effective reproduction numbers

BackgroundThe effective reproduction number (Re) serves as a metric of population-wide, time-varying disease spread. During the COVID-19 pandemic, Re was primarily estimated from clinical surveillance data streams (Rcc), which have varied in quality and representativeness due to changes in testing volume, test-seeking behavior, and resource constraints. Deriving Re from alternative data sources such as wastewater could inform future public health responses. ObjectivesWe estimated county-aggregated, sewershed-restricted wastewater-based SARS-CoV-2 Re (Rww) from May 1, 2022 to April 30, 2023 for five counties in California of varying population sizes, clinical testing rates, demographics, proportions surveilled by wastewater, and sampling frequencies to validate the reliability of Rww as a real-time disease surveillance metric. MethodsWe produced both instantaneous and cohort sewershed-restricted Re using smoothed and deconvolved wastewater concentrations. We then population-weighted and aggregated these sewershed-level estimates to arrive at county-level Re. Using mean absolute error (MAE), Spearmans rank correlation ({rho}), confusion matrix classification, and cross-correlation analyses, we compared the timing and trajectory of two Rww models to: (1) a publicly available, county-level ensemble of Rcc estimates, and (2) a county-aggregated, sewershed-restricted Rcc. ResultsBoth Rww models demonstrated high concordance with traditional Rcc estimates, as indicated by low mean absolute errors (MAE [&le;] 0.09), significant positive Spearman correlation (Spearman {rho} [&ge;] 0.66, p < 0.001), and high confusion matrix classification accuracy ([&ge;] 0.81). The relative timings of Rwwand Rcc were less clear, with cross-correlation analyses suggesting strong associations for a wide range of temporal lags that varied by county and Rww model type. DiscussionThis Re estimation methodology provides a generalizable, robust, and operationalizable framework for estimating county-level Rww. Our results support the additional use of Rwwas an epidemiological tool for surveillance. Based on this research, we produced publicly available Rww nowcasts for the California Communicable diseases Assessment Tool (https://calcat.covid19.ca.gov/cacovidmodels/).