Kinetics of SARS-CoV-2 infection in the human upper and lower respiratory tracts and their relationship with infectiousness
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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.
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SciScore for 10.1101/2020.09.25.20201772: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The probabilistic model we developed represents a first step to link viral load to SARS-CoV-2 infectiousness, but it has limitations. First, the model used a Michaelis-Menten term to model the saturation effect for simplicity. The data we used to support this functional form were limited and other functional forms incorporating a …
SciScore for 10.1101/2020.09.25.20201772: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The probabilistic model we developed represents a first step to link viral load to SARS-CoV-2 infectiousness, but it has limitations. First, the model used a Michaelis-Menten term to model the saturation effect for simplicity. The data we used to support this functional form were limited and other functional forms incorporating a saturation effect may also be able to explain the data. Second, the model makes several simplifying assumptions including assuming that all contacts are of the same duration and the parameter values in the model are the same across patients, whereas in reality, there may exist considerable heterogeneity (43, 58). Therefore, further model developments incorporating different aspects of heterogeneity in the transmission process (40, 58), rigorous parameter estimation from clinical and epidemiological data, and testing of alternative models are warranted. The viral load in the LRT is maintained at intermediate-to-high levels for a prolonged period of time (5, 16). In Ref. (5), multiple viral peaks in the LRT were observed in several patients. We tested different hypotheses to explain this observation by constructing mathematical models that include the immune responses, proliferation of target cells or spatial spread of virus in the lungs. The best model for explaining the data is the one that implicitly considers spatial spread of virus in the lungs. If virus can reach new physiological compartments, e.g. different regions of the lungs, then new target...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
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