Estimating unreported SARS-CoV-2 infections in Austria using wastewater-based epidemiology

Wastewater-based epidemiology offers a comprehensive yet cost-effective way to monitor pathogen circulation. However, it is not entirely clear how wastewater signals can be reliably mapped to case numbers and therefore to incidence. Here, we aim to estimate the number of total SARS-CoV-2 infections including reported and unreported cases in Austria by analysing two different longitudinal wastewater datasets covering 113 wastewater treatment plants from October 2021 to October 2022. These plants cover most of the Austrian population, which had one of the highest per capita testing rates during the Coronavirus Disease 2019 (COVID-19) pandemic. We empirically find that the relationship between reported COVID-19 cases and viral load in wastewater is significantly influenced by the number of tests performed. Based on this observation, we developed a method for estimating total cases by scaling reported cases by test activity and accounting for periods when different viral variants were dominant. We find that the ratio of estimated total to reported cases increased substantially over time, from a value around 1.49 at the peak of the BA.2 wave to a value of 5.48 at the peak of the BA.5 wave, and validate these results in two datasets. Our results also suggest that there was less shedding per case in periods where BA.5 was dominant than in periods where BA.1 and BA.2 were dominant, which in turn showed less shedding than in periods dominated by the Delta variant. The results of this study provide critical insight into the potential of wastewater measurements to provide a more accurate assessment of the dynamics of infectious disease transmission.