PraneshPadmanabhan2022 - SARS-CoV-2 virus dynamics model (human)

  public model
Model Identifier
MODEL2205010001
Short description
SARS-CoV-2 virus dynamics ODE model parameterized using non-linear mixed effects fitting to longitudinal human data.
Format
MATLAB (Octave)
Related Publication
  • Modeling how antibody responses may determine the efficacy of COVID-19 vaccines
  • Pranesh Padmanabhan, Rajat Desikan, Narendra M. Dixit
  • Nature Computational Science , 2/ 2022 , Volume 2 , Issue 2 , pages: 123--131 , DOI: 10.1038/s43588-022-00198-0
  • 1Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia. 2Department of Chemical Engineering, Indian Institute of Science, Bangalore, India. 3Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore, India.
  • Predicting the efficacy of COVID-19 vaccines would aid vaccine development and usage strategies, which is of importance given their limited supplies. Here we develop a multiscale mathematical model that proposes mechanistic links between COVID-19 vaccine efficacies and the neutralizing antibody (NAb) responses they elicit. We hypothesized that the collection of all NAbs would constitute a shape space and that responses of individuals are random samples from this space. We constructed the shape space by analyzing reported in vitro dose–response curves of ~80 NAbs. Sampling NAb subsets from the space, we reca- pitulated the responses of convalescent patients. We assumed that vaccination would elicit similar NAb responses. We devel- oped a model of within-host SARS-CoV-2 dynamics, applied it to virtual patient populations and, invoking the NAb responses above, predicted vaccine efficacies. Our predictions quantitatively captured the efficacies from clinical trials. Our study thus suggests plausible mechanistic underpinnings of COVID-19 vaccines and generates testable hypotheses for establishing them.
Contributors
Submitter of the first revision: Rajat Desikan
Submitter of this revision: Rajat Desikan
Modellers: Rajat Desikan

Metadata information


Curation status
Non-curated


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Model files

2022 Nature Comp Sci.pdf My paper in Nature Computational Science about COVID virus dynamics models. The paper contains a github link with all model codes. 4.50 MB Preview | Download

  • Model originally submitted by : Rajat Desikan
  • Submitted: May 1, 2022 4:42:13 PM
  • Last Modified: May 1, 2022 4:42:13 PM
Revisions
  • Version: 1 public model Download this version
    • Submitted on: May 1, 2022 4:42:13 PM
    • Submitted by: Rajat Desikan
    • With comment: Import of PraneshPadmanabhan2022 - SARS-CoV-2 virus dynamics model (human)