Abstract
SARS-CoV-2 is a human pathogen that causes infection in both the upper respiratory tract (URT) and the lower respiratory tract (LRT). The viral kinetics of SARS-CoV-2 infection and how they relate to infectiousness and disease progression are not well understood. Here, we develop data-driven viral dynamic models of SARS-CoV-2 infection in both the URT and LRT. We fit the models to viral load data from patients with likely infection dates known, we estimated that infected individuals with a longer incubation period had lower rates of viral growth, took longer to reach peak viremia in the URT, and had higher chances of presymptomatic transmission. We then developed a model linking viral load to infectiousness. We found that to explain the substantial fraction of transmissions occurring presymptomatically, a person’s infectiousness should depend on a saturating function of the viral load, making the logarithm of the URT viral load a better surrogate of infectiousness than the viral load itself. Comparing the roles of target-cell limitation, the innate immune response, proliferation of target cells and spatial infection in the LRT, we found that spatial dissemination in the lungs is likely to be an important process in sustaining the prolonged high viral loads. Overall, our models provide a quantitative framework for predicting how SARS-CoV-2 within-host dynamics determine infectiousness and represent a step towards quantifying how viral load dynamics and the immune responses determine disease severity.
Significance A quantitative understanding of the kinetics of SARS-CoV-2 infection is key to understanding the development of infectiousness and disease symptoms. To address this need, we developed data-driven within-host models of SARS-CoV-2 infection and showed that lower rates of viral growth lead to longer incubation periods and higher chances of presymptomatic transmission. We found that the logarithm of the URT viral load serves an appropriate surrogate for a person’s infectiousness. We then developed a mechanistic model for infectiousness and showed that a saturation effect in the dependence of transmission on viral load gives rise to this relationship. We also provide evidence of spatial dissemination in the lungs as an important process in sustaining prolonged high viral loads in the LRT.
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
Portions of this work were done under the auspices of the U.S. Department of Energy through Los Alamos National Laboratory, which is operated by Triad National Security, LLC, for the National Nuclear Security Administration of the U.S. Department of Energy (contract No. 89233218CNA000001). The work was supported by the Laboratory Directed Research and Development program of Los Alamos National Laboratory (project No. 20200743ER and 20200695ER), and by the Defense Advanced Research Projects Agency (contract No. HR0011938513). Part of this research was supported by the DOE Office of Science through the National Virtual Biotechnology Laboratory, a consortium of DOE national laboratories focused on response to COVID-19, with funding provided by the Coronavirus CARES Act.
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Data Availability
The data are available in the manuscript and the supplementary materials.
