Modeling within-host SARS-CoV-2 dynamics and the relationship between viral load and a person's infectiousness

The within-host viral kinetics of SARS-CoV-2 infection and how they relate to a person’s infectiousness are not well understood. This limits our ability to quantify the impact of interventions on viral transmission.We developed variety of viral dynamic models of SARS-CoV-2 infection in both the upper and lower respiratory tracts (URT and LRT) to gain a quantitative understanding of the infection dynamics of SARS-CoV-2. The models we studied compared the roles of target-cell limitation versus the roles of the innate and the adaptive immune response as well as the role of spatial infection in the LRT. We fit these models to clinical data to estimate key within-host parameters such as the infected cell half-life and the within-host reproductive number. We then develop a model linking viral load (VL) in the URT to infectiousness and showed a person’s infectiousness increases sub-linearly with VL and that the logarithm of the VL in the upper respiratory tract (URT) is a better surrogate of infectiousness than the VL itself.  Overall, our models provide a quantitative framework for inferring the impact of therapeutics and vaccines that lower VL on the infectiousness of individuals and for evaluating rapid testing strategies.