Fatehi, F, Bingham, RJ, Dykeman, EC et al. (2 more authors) (2021) Comparing antiviral strategies against COVID-19 via multiscale within-host modelling. Royal Society Open Science, 8 (8). 210082. ISSN 2054-5703
Abstract
Within-host models of COVID-19 infection dynamics enable the merits of different forms of antiviral therapy to be assessed in individual patients. A stochastic agent-based model of COVID-19 intracellular dynamics is introduced here, that incorporates essential steps of the viral life cycle targeted by treatment options. Integration of model predictions with an intercellular ODE model of within-host infection dynamics, fitted to patient data, generates a generic profile of disease progression in patients that have recovered in the absence of treatment. This is contrasted with the profiles obtained after variation of model parameters pertinent to the immune response, such as effector cell and antibody proliferation rates, mimicking disease progression in immunocompromised patients. These profiles are then compared with disease progression in the presence of antiviral and convalescent plasma therapy against COVID-19 infections. The model reveals that using both therapies in combination can be very effective in reducing the length of infection, but these synergistic effects decline with a delayed treatment start. Conversely, early treatment with either therapy alone can actually increase the duration of infection, with infectious virions still present after the decline of other markers of infection. This suggests that usage of these treatments should remain carefully controlled in a clinical environment.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
Keywords: | intercellular infection model; adaptive immune response; intracellular infection model; COVID-19 |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Molecular and Cellular Biology (Leeds) > Biological Chemistry (Leeds) |
Funding Information: | Funder Grant number Wellcome Trust 110145/Z/15/Z |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Aug 2021 11:06 |
Last Modified: | 25 Jun 2023 22:43 |
Status: | Published |
Publisher: | The Royal Society |
Identification Number: | 10.1098/rsos.210082 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:176799 |