Abstract: The effective reproductive number, Re, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, Re estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. Here we show that the dynamics of SARS-CoV-2 RNA in wastewater can be used to estimate Re in near real-time, independent of clinical data and without associated biases stemming from clinical testing and reporting strategies. The method to estimate Re from wastewater is robust and applicable to data from different countries and wastewater matrices. The resulting estimates are as similar to the Re estimates from case report data as Re estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer Re. To our knowledge, this is the first time Re has been estimated from wastewater. This method provides a low cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens. Significance statementThe effective reproductive number, Re, is widely used during the COVID-19 pandemic to track disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. Re is typically estimated from clinical case data, and can be biased by e.g. changes in testing and reporting. We show longitudinal measurements of SARS-CoV-2 RNA in wastewater can be used to estimate Re, across different regions, and provide an independent assessment of the dynamics of COVID-19. Given widespread wastewater sampling during this pandemic, these Re estimates are directly applicable as a rapid, low-cost method to inform public health policy. The method can be adapted to other pathogens, including those for which clinical data is not available.
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