ArticlePLoS pathogens2022
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.
Article in PLoS pathogens, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 38 citations in OpenAlex.
- Heterogeneous immune recovery after viral response through a dynamical model of feedback-driven persistence and clearance.Frontiers in immunology · 2026Article
- Viral Dynamic Models During COVID-19: Are We Ready for the Next Pandemic?CPT: pharmacometrics & systems pharmacology · 2025Review
- Epitope mapping of SARS-CoV-2 Spike protein using naturally-acquired immune responses to develop monoclonal antibodies.Scientific reports · 2025Article
- Modeling suggests SARS-CoV-2 rebound after nirmatrelvir-ritonavir treatment is driven by target cell preservation coupled with incomplete viral clearance.Journal of virology · 2025Article
- Modelling and investigating memory immune responses in infectious disease. Application to influenza a virus and sars-cov-2 reinfections.Infectious Disease Modelling · 2025Article
- A biomathematical model of SARS-CoV-2 in Syrian hamsters.Scientific reports · 2024Article
- The kinetics of SARS-CoV-2 infection based on a human challenge study.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Unveiling coagulation dysfunction in patients with COVID-19: a retrospective analysis.Journal of medicine and life · 2024Article
- Modelling HIV-1 control and remission.NPJ systems biology and applications · 2024Review
- Article
- Mechanistic modeling projections of antibody persistence after homologous booster regimens of COVID-19 vaccine Ad26.COV2.S in humans.CPT: pharmacometrics & systems pharmacology · 2023Article
- Dynamical modelling of viral infection and cooperative immune protection in COVID-19 patients.PLoS computational biology · 2023Article
- Anti-inflammatory effects of dexamethasone in COVID-19 patients: Translational population PK/PD modeling and simulation.Clinical and translational science · 2023Article
- Making waves: Integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks.Water research · 2023Article
- Relationship between the inclusion/exclusion criteria and sample size in randomized controlled trials for SARS-CoV-2 entry inhibitors.Journal of theoretical biology · 2023Article
- Mechanistic model for booster doses effectiveness in healthy, cancer, and immunosuppressed patients infected with SARS-CoV-2.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- A simple model of COVID-19 explains disease severity and the effect of treatments.Scientific reports · 2022Article
- Mechanistic Models of COVID-19: Insights into Disease Progression, Vaccines, and Therapeutics.International journal of antimicrobial agents · 2022Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.