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Heterogeneous SARS-CoV-2 kinetics due to variable timing and intensity of immune responses
Katherine Owens, … , Shadisadat Esmaeili, Joshua T. Schiffer
Katherine Owens, … , Shadisadat Esmaeili, Joshua T. Schiffer
Published April 4, 2024
Citation Information: JCI Insight. 2024;9(9):e176286. https://doi.org/10.1172/jci.insight.176286.
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Research Article Infectious disease Virology

Heterogeneous SARS-CoV-2 kinetics due to variable timing and intensity of immune responses

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Abstract

The viral kinetics of documented SARS-CoV-2 infections exhibit a high degree of interindividual variability. We identified 6 distinct viral shedding patterns, which differed according to peak viral load, duration, expansion rate, and clearance rate, by clustering data from 768 infections in the National Basketball Association cohort. Omicron variant infections in previously vaccinated individuals generally led to lower cumulative shedding levels of SARS-CoV-2 than other scenarios. We then developed a mechanistic mathematical model that recapitulated 1,510 observed viral trajectories, including viral rebound and cases of reinfection. Lower peak viral loads were explained by a more rapid and sustained transition of susceptible cells to a refractory state during infection as well as by an earlier and more potent late, cytolytic immune response. Our results suggest that viral elimination occurs more rapidly during Omicron infection, following vaccination, and following reinfection due to enhanced innate and acquired immune responses. Because viral load has been linked with COVID-19 severity and transmission risk, our model provides a framework for understanding the wide range of observed SARS-CoV-2 infection outcomes.

Authors

Katherine Owens, Shadisadat Esmaeili, Joshua T. Schiffer

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Figure 6

Model fitting to viral rebound in the NBA cohort.

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Model fitting to viral rebound in the NBA cohort.
(A) We classified infe...
(A) We classified infections as examples of viral rebound if there were at least 2 peaks in the model simulation with height of 3 logs and prominence of 0.5 log. (B–F) Mean number of susceptible cells (B), number of active infected cells (C), number of target cells that are refractory (D), viral load (E), and rate of late clearance (F) as predicted by our mathematical model for rebound versus nonrebound cases in red and blue, respectively. The 95% CI is shaded. (G) Distribution of individual parameter estimates for the rebound versus nonrebound cases. Only those for which the mean differs significantly are displayed (P < 0.05 for Mann-Whitney U test with Bonferroni adjustment for multiple comparisons).

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