Background: Wastewater-based surveillance complements case-based surveillance systems by capturing pathogen signals shed in stool, enabling population-level monitoring independent of clinical testing. Its utility during the COVID-19 pandemic has been widely explored, but its responsiveness and interpretability relative to case-based systems remain insufficiently understood. Methods: We analyzed data on COVID-19 or SARS-CoV-2 from July 2022 to December 2024 across 131 weeks, using wastewater surveillance and four case-based surveillance systems. These comprise syndromic surveillance systems at the population as well as the primary care level, and notification data, all aimed at monitoring COVID-19 incidence in Germany. We assessed agreement between wastewater viral load and disease incidence using visual inspection, cross-correlation analysis, and an estimated prevalence dynamic informed by a literature-based fecal shedding model. We derived retrospective translation factors and compared week-to-week trend directions between systems. Finally, we tested the predictive power of wastewater data using classification models to anticipate current week incidence trends. Results: Wastewater SARS-CoV-2 viral load closely correlates with COVID-19 incidence trends from case-based systems, showing similar timing of peaks and troughs without notable time lags. Cross-correlation coefficients are highest with syndromic surveillance systems (up to 0.87) and lowest with notification data (0.43). Retrospective translation into incidence estimates works well on average, but week-to-week translation varies considerably. Wastewater-based models correctly predict the current week trend, as indicated by at least three of the four case-based systems, with about 68\% probability. Conclusion: Wastewater surveillance correlates well with COVID-19 incidence, but real-time translation to incidence lacks precision. Trend prediction for the current week may demonstrate improved accuracy and may be valuable when case reporting is limited or delayed.
Abunijela et al. (Thu,) studied this question.