ArticlePLoS computational biology2023
Dynamical modelling of viral infection and cooperative immune protection in COVID-19 patients.
Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 18 citations in OpenAlex.
- Circadian Disruption Exacerbates Innate Immune Responses by Modulating the Bistability of Pro-Inflammatory Signaling: A Dynamical Modeling Study.Biomedicines · 2026Article
- Ordinary differential equation models of SARS-CoV-2 replication dynamics and antiviral drug efficacies.Npj viruses · 2026Review
- Heterogeneous immune recovery after viral response through a dynamical model of feedback-driven persistence and clearance.Frontiers in immunology · 2026Article
- A Systematic Computational Framework for Practical Identifiability Analysis in Mathematical Models Arising from Biology.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Linear scaling reveals low-dimensional structure in observable microbial dynamics.bioRxiv : the preprint server for biology · 2025Article
- Article
- A Modular Mathematical Model of the Immune Response for Investigating the Pathogenesis of Infectious Diseases.Viruses · 2025Article
- Quantitative cancer-immunity cycle modeling for predicting disease progression in advanced metastatic colorectal cancer.NPJ systems biology and applications · 2025Article
- Mathematical modelling of the heterogeneity of disease progression and treatment outcomes in patients with COVID-19.Frontiers in microbiology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Once challenged by the SARS-CoV-2 virus, the human host immune system triggers a dynamic process against infection. We constructed a mathematical model to describe host innate and adaptive immune response to viral challenge. Based on the dynamic properties of viral load and immune response, we classified the resulting dynamics into four modes, reflecting increasing severity of COVID-19 disease. We found the numerical product of immune system's ability to clear the virus and to kill the infected cells, namely immune efficacy, to be predictive of disease severity. We also investigated vaccine-induced protection against SARS-CoV-2 infection. Results suggested that immune efficacy based on memory T cells and neutralizing antibody titers could be used to predict population vaccine protection rates. Finally, we analyzed infection dynamics of SARS-CoV-2 variants within the construct of our mathematical model. Overall, our results provide a systematic framework for understanding the dynamics of host response upon challenge by SARS-CoV-2 infection, and this framework can be used to predict vaccine protection and perform clinical diagnosis.
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Registered trials
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.