Integrating wastewater-based epidemiology and mechanistic models: Implications for public health and multi-strain dynamics

Wastewater-based epidemiology (WBE) is an emerging tool for community disease surveillance. WBE has become prominent during the COVID-19 pandemic as a near-real time, cost-effective method for surveillance which works synergistically with clinical data. Community transmission and variant emergence may be monitored through quantifying and sequencing viral particles shed via stool by infected individuals. First, connect a standard epidemic SEIR model to the dynamics of viral RNA in the sewer shed. Using data from the greater Boston area from October 2020 to January 2021, we show that this model captures the temporal fluctuations of viral particles with prevalence peaking earlier and higher than reported. We later use a two-strain SIR model with time delay to study the circulation of two strains.

We provide local and global stability results and validate the model using WBE.