In many jurisdictions, the surveillance of the COVID-19 pandemic has relied mostly on the identification of clinical cases through diagnostic testing and contact tracing. However, as shown during the Omicron wave, clinical surveillance can be overwhelmed during large waves of infections. Fecal shedding during SARS-CoV-2 infections allows to approximate prevalence levels in a community by sampling its wastewater. The Public Health Agency of Canada/National Microbiology Laboratory (PHAC/NML) leads a national wastewater surveillance program for COVID-19 in Canada. This data stream allowed us to develop a mathematical model that integrates wastewater data and traditional clinical data to better triangulate the COVID-19 epidemic across multiple large cities in Canada. This presentation will describe the modelling framework along its data pipeline at PHAC/NML and provide examples of how insights from modelling supported COVID-19 surveillance.

Bio: Dr. David Champredon is a senior scientist at the Public Health Agency of Canada. His work focuses on modelling the spread of infectious diseases at the population level, especially respiratory and sexually transmitted infections. During the past two years, he supported the modelling efforts to respond to the COVID-19 pandemic, particularly wastewater-based modelling.