A new paper from the Germ Lab is out!
Check out the work led by PhD candidate William Chen: Making waves: Establishing a modeling framework to evaluate novel targets for wastewater-based surveillance
In this work, Chen and Bibby proposed an analysis framework for the use of wastewater-based surveillance (WBS) in identifying diseases suitable for WBS applications. They explored five key factors that impact the likelihood of detecting diseases through WBS monitoring: the rate of shedding genetic material into wastewater, the rate of infection in the population, per capita wastewater generation, the limit of detection within the testing process (PLOD), and the number of PCR replicates used. This knowledge is aimed to assist researchers and stakeholders in addressing the inherent uncertainties associated with wastewater monitoring and can lead to improvements in WBS outcomes. Ultimately, this supports future investments and the expansion of WBS research, especially in the context of emerging diseases.
