Xu, J., Lopez Garcia, M. orcid.org/0000-0003-3833-8595, House, T. et al. (1 more author) (2025) Modelling the dynamics of SARS-CoV-2 during the first 14 days of infection. Epidemics: The Journal on Infectious Disease Dynamics, 52. 100843. ISSN: 1755-4365
Abstract
Interpreting the viral mechanism of SARS-CoV-2 based on the human body level is critical for developing more efficient interventions. Due to the limitation of data, limited models consider the viral dynamics of the early phase of infection. The Human Challenge Study (Killingley et al., 2022) enables us to obtain data from inoculation to the 14th day after infection, which provides an overview of the dynamics of SARS-CoV-2 infection within the host. In the Human Challenge Study, each volunteer was inoculated with 10TCID50, approximately 55PFU, of a wild-type of virus (Killingley et al., 2022), and the data indicates that the viral load reduced below the detectable level within a day. The simplified within-host models developed by Xu et al. (2023) explain the data from the Human Challenge Study (Killingley et al., 2022). However, they do not explain the viral decay from Day 0 to Day 1. Hence, in this paper, we aim to develop a new viral mechanism to explain this phenomenon. Based on the simplified within-host models developed by Xu et al. (2023), we consider that the virus will first go through an adjustment phase and then start to replicate. A new dose-response model is developed to evaluate the probability of infection by constructing a boundary problem. We will discuss this viral mechanism and fit the model to the data of the Human Challenge Study (Killingley et al., 2022) by adopting AMC-SMC (approximate Bayesian computation-sequential Monte Carlo). Based on the results of parameter inference, we estimate that the adjusted viral load is around 1% of the inoculated viral load.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2025 The Authors. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Within-host models, Dose-response, SARS-coV-2 |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/V032658/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 16 Jul 2025 09:25 |
Last Modified: | 12 Aug 2025 13:24 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.epidem.2025.100843 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:229168 |