Informing risk stratification and vaccine policy via a predictive mathematical model of SARS-COV-2 infection
Year: 2026
Type: preprint
Abstract: SARS-CoV-2 human challenge studies enabled unprecedented high frequency temporal measurements of immune determinants of viral control. We integrated prior knowledge of SARS-CoV-2 replication, innate, cytotoxic T cell and antibody responses into a dynamic model which captured viral-load kinetics in seronegative volunteers challenged with wildtype virus. The model predicted measured innate and adaptive immune dynamics. Perturbation analyses indicated that innate immunity limits peak viral load, whereas antibodies principally mediate clearance while cytotoxic T cells become critical in antibody deficiency. Pre-existing antibodies suppressed both viral replication and subsequent immune activation- a prediction validated in a second challenge study of seropositive participants infected with the SARS-CoV-2 Delta variant. The model explains how specific immunodeficiencies may increase susceptibility to severe or persistent infection, supporting clinical risk stratification. It suggests that T cell-targeted vaccination strategies may provide limited protection without effective neutralising antibodies, and that attenuated boosting after low-dose exposure requires repeated vaccination to reduce breakthrough infections, informing public health policy. One Sentence Summary A mathematical model of SARS-COV-2 infection predicts innate and adaptive immunity, and informs risk stratification and vaccine policy.
Source: medRxiv
Authors: Benny Chain, Curtis G. Callan, David Scobie, Matthew V. Cowley, Jana Jiang, Rishi K. Gupta, Carolin T. Turner, Joshua Rosenheim, Clare Thakker, Lucy Bell, Gayathri Nageswaran, Suzanne Byrne, Ben Killingley, Mariya Kalinova, Alison Boyers, Andrew Catchpole, Alex Mann, Rik G. H. Lindeboom, Marko Z. Nikolic, Sarah A. Teichmann, Helen Wagstaffe, Andreas Tiffeau-Mayer, Christopher Chiu, Mahdad Noursadeghi
Institutions: University College London, Princeton University, École Normale Supérieure - PSL, University College Hospital, University College London Hospitals NHS Foundation Trust, hVIVO (United Kingdom), Wellcome Sanger Institute, The Netherlands Cancer Institute, Canadian Institute for Advanced Research, Wellcome/MRC Cambridge Stem Cell Institute, University of Cambridge, Imperial College London
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funders: Princeton University, Wellcome Trust, Royal Free London NHS Foundation Trust, New Zealand Government, National Institute for Health Research Health Protection Research Unit, National Institute for Health and Care Research, Imperial College London, Imperial College Healthcare NHS Trust, University of Oxford, Rosetrees Trust, University of Liverpool, Public Health England, Ministerie van Volksgezondheid, Welzijn en Sport, Medical Research Council, NIHR Imperial Biomedical Research Centre
Awards: G1204445118, Genomic and transcriptomic determinants of host susceptibility, protection, and viral mutation in experimental SARS CoV-2 infection, Genomic and transcriptomic determinants of host susceptibility, protection, and viral mutation in experimental SARS CoV-2 infection, G1962299536, Delineating late foetal human lung development and maturation, G310335178, Clinical Characterisation of COVID-19 admitted to hospitals in the United Kingdom, G4367455379, G4388622794, G5208948526, G6091644065, G6377572816, G7725255074, G7835552818, G7898200040, G8038231773, G8180283288, G8372072663, G869621869, In vivo and in situ modelling of endoplasmic reticulum shaping defects on mitochondrial function in hereditary spastic paraplegias, G966130949
OpenAlex ID: W7221790801