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.


Mathematical Biology Seminar
Friday, April 14
WXLR A302 and virtual via Zoom
(This talk will be presented  in-person)


Samantha Brozak
PhD Student, Applied Mathematics
School of Mathematical and Statistical Sciences
Arizona State University