Within-host models of SARS-CoV-2: What can it teach us on the biological factors driving virus pathogenesis and transmission?

Prague, Mélanie; Alexandre, Marie; Thiébaut, Rodolphe; Guedj, Jérémie

doi:10.1016/j.accpm.2022.101055

Cited by 8 publications

(5 citation statements)

References 28 publications

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“…Accounting for the latter process in our model (by adding the term −δI � to right hand side of Eq 5) and using the next generation matrix method [70], we derived R 0 ¼ k 1 =ðE � 0 þ dÞ. Using the above parameter values, we estimated R 0 � k 1 d � 13 À 15, consistent with current estimates of R 0 �10 [71], and similar for both mildly and severely infected patients we examined. Thus, the differences in severity appeared to arise from the differences in the immune responses 'after' the initial stages of infection.…”

Section: Plos Pathogenssupporting

confidence: 64%

Modeling recapitulates the heterogeneous outcomes of SARS-CoV-2 infection and quantifies the differences in the innate immune and CD8 T-cell responses between patients experiencing mild and severe symptoms

2022

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SARS-CoV-2 infection results in highly heterogeneous outcomes, from cure without symptoms to acute respiratory distress and death. Empirical evidence points to the prominent roles of innate immune and CD8 T-cell responses in determining the outcomes. However, how these immune arms act in concert to elicit the outcomes remains unclear. Here, we developed a mathematical model of within-host SARS-CoV-2 infection that incorporates the essential features of the innate immune and CD8 T-cell responses. Remarkably, by varying the strengths and timings of the two immune arms, the model recapitulated the entire spectrum of outcomes realized. Furthermore, model predictions offered plausible explanations of several confounding clinical observations, including the occurrence of multiple peaks in viral load, viral recrudescence after symptom loss, and prolonged viral positivity. We applied the model to analyze published datasets of longitudinal viral load measurements from patients exhibiting diverse outcomes. The model provided excellent fits to the data. The best-fit parameter estimates indicated a nearly 80-fold stronger innate immune response and an over 200-fold more sensitive CD8 T-cell response in patients with mild compared to severe infection. These estimates provide quantitative insights into the likely origins of the dramatic inter-patient variability in the outcomes of SARS-CoV-2 infection. The insights have implications for interventions aimed at preventing severe disease and for understanding the differences between viral variants.

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Section: Plos Pathogenssupporting

confidence: 64%

Modeling recapitulates the heterogeneous outcomes of SARS-CoV-2 infection and quantifies the differences in the innate immune and CD8 T-cell responses between patients experiencing mild and severe symptoms

2022

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“…8 Within-host kinetics: the epidemic within When thinking about a pandemic virus and its evolution, what comes to mind is its spread in human populations. However, from the virus' point of view, the dynamics taking place in the host are equally important [147]. We will not describe the pathology of the infection or the interaction between virions and the host cells, but rather present what we know of the `epidemic within'.…”

Section: From Game-changing Vaccines To Immune Escapementioning

confidence: 99%

SARS-CoV-2 epidemiology, kinetics, and evolution: a narrative review

Alizon,

Sofonea

2024

Preprint

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Since winter 2019, SARS-CoV-2 emerged, spread, and evolved all around the globe. We explore four years of evolutionary epidemiology of this virus, ranging from the applied public health challenges to the more conceptual evolutionary biology perspectives. Through this review, we revisit key episodes of the pandemic, highlighting important epidemiology and evolution notions they may raise, to discuss how the pandemic has transformed (or should transform) the surveillance and prevention of viral respiratory infections.

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“…The studies discussed above, and many others [46] , [47] , [48] , [49] , [50] (see also the recent perspective paper by Prague et al [51] ), highlight the use of mathematical modelling of the immune response to establish effective schedules or public-health vaccination strategies. However, a limitation of these deterministic models is their inability to capture the impact of stochasticity in COVID-19 severity.…”

Section: Within Host-modelling In the Two Years Of The Covid-19 Pandemicmentioning

confidence: 99%

The race to understand immunopathology in COVID-19: Perspectives on the impact of quantitative approaches to understand within-host interactions

et al. 2023

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Within-host models of SARS-CoV-2: What can it teach us on the biological factors driving virus pathogenesis and transmission?

Cited by 8 publications

References 28 publications

Modeling recapitulates the heterogeneous outcomes of SARS-CoV-2 infection and quantifies the differences in the innate immune and CD8 T-cell responses between patients experiencing mild and severe symptoms

Modeling recapitulates the heterogeneous outcomes of SARS-CoV-2 infection and quantifies the differences in the innate immune and CD8 T-cell responses between patients experiencing mild and severe symptoms

SARS-CoV-2 epidemiology, kinetics, and evolution: a narrative review

The race to understand immunopathology in COVID-19: Perspectives on the impact of quantitative approaches to understand within-host interactions

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