1 Sainte-Justine University Hospital Research Centre, Montréal, Québec, Canada.
2 Department of Mathematics and Statistics, Université de Montréal, Montréal, Québec, Canada.
3 Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America.
4 Department of Physiology, McGill University, Montréal, Québec, Canada.
5 Department of Mathematics and Statistics, Concordia University, Montréal, Québec, Canada.
6 Department of Immunology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
7 Natural Science Division, Pepperdine University, Malibu, California, United States of America.

To understand the diversity of immune responses to SARS-CoV-2 and distinguish features that predispose individuals to severe COVID-19, we developed a mechanistic, within-host mathematical model and virtual patient cohort. Our results suggest that virtual patients with low production rates of infected cell derived IFN subsequently experienced highly inflammatory disease phenotypes, compared to those with early and robust IFN responses. In these in silico patients, the maximum concentration of IL-6 was also a major predictor of CD8+ T cell depletion. Our analyses predicted that individuals with severe COVID-19 also have accelerated monocyte-to-macrophage differentiation mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings suggest biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation.