You are here

MIA Talks

Primer: Using viral loads and within-host models to improve COVID-19 surveillance

March 10, 2021
Center for Communicable Disease Dynamics, Harvard Chan School of Public Health

Limited testing capacity has been an ongoing problem throughout the COVID-19 pandemic. Pooled testing is a faster and less expensive diagnostic approach compared to individual testing, but there are important tradeoffs in sensitivity, efficiency and logistics to consider. In this talk, I outline an approach combining within-host hierarchical models, compartmental models of pathogen spread, and viral load data to identify optimized pooling protocols that are robust to the changing state of an epidemic. This study highlights the importance of considering within-host biology and individual-level heterogeneity when evaluating epidemiological surveillance strategies.