Evolving Wastewater-Based Epidemiology: From Pandemic Surveillance Towards One Health

Since the onset of the SARS-CoV-2 pandemic, wastewater-based epidemiology (WBE) has emerged as a valuable tool for tracking infectious disease outbreaks by quantifying human biomarkers in wastewater. A harmonized workflow, encompassing all stages from sample collection to data visualization, is critical for ensuring reliable results.
To achieve this, we developed a GIS-based data model that integrates the entire WBE process, from sampling to data visualization. This system, created in collaboration with public health authorities, has demonstrated its effectiveness in pandemic response efforts. Given the natural variability of wastewater data due to the complex dynamics of sewer systems, we incorporated an automated quality control algorithm designed to filter out potential outliers based on predefined criteria.
A key focus of our research is understanding the influence of sewer system characteristics and sampling strategies on biomarker concentrations. We hypothesize that community size and sewer network length significantly impact the diurnal variability of biomarker levels. To test this, 48-hour sampling campaigns were conducted in seven communities across southern Germany, measuring SARS-CoV-2 biomarkers and additional surrogate parameters, such as indicator viruses and chemical tracers, to explore normalization strategies. Results suggest that smaller communities exhibit greater diurnal variability in biomarker concentrations, likely due to shorter retention times within the sewer network.
Additionally, our methodology is being expanded to include new biomarkers, such as antibiotic-resistance genes. This extension aims to broaden the scope of WBE within a One Health framework, enhancing its potential for comprehensive public health surveillance.