Models to inform wastewater-based epidemiology: identifiability, uncertainty, and opportunities
Wastewater monitoring has seen a broad expansion over the pandemic as a useful tool for understanding disease patterns, without relying on clinical testing or care-seeking. Wastewater data has great potential to help us understand the epidemiological patterns of a wide range of diseases—from detecting new outbreaks to understanding seasonal patterns. But challenges remain in understanding how to translate wastewater concentration data into population information on transmission patterns. In this talk, we will explore how mathematical models have the potential to help us bridge that gap and make wastewater data more actionable and interpretable, and examine the uncertainty and identifiability challenges involved in linking models with wastewater data.