bioRxivImmunologyPreprint
Global Sensitivity Analysis of the Onset of Nasal Passage Infection by SARS-CoV-2 With Respect to Heterogeneity in Host Physiology and Host Cell-Virus Kinetic Interactions
L. Zhang, H. Cao, K. Medlin, J. Pearson, A. Aristotelous, A. Chen, T. Wessler, M. G. Forest
Abstract
Throughout the COVID-19 pandemic, positive nasal swab tests have revealed dramatic population heterogeneity in viral titers spanning 6 orders-of-magnitude. Our goal here is to probe potential drivers of infection outcome sensitivity arising from (i) physiological heterogeneity between hosts and (ii) host-variant heterogeneity in the detailed kinetics of cell infection and viral replication. Toward this goal, we apply global sensitivity methods (Partial Rank Correlation Coefficient analysis and Latin Hypercube Sampling) to a physiologically faithful, stochastic, spatial model of inhaled SARS-CoV-2 exposure and infection in the human respiratory tract. We focus on the nasal passage as the primary origin of respiratory infection and site of clinical testing, and we simulate the spatial and dynamic progression of shed viral load and infected cells in the immediate 48 hours post infection. We impose immune evasion, i.e., suppressed immune protection, based on the preponderance of clinical evidence that nasal infections occur rapidly post exposure, largely independent of immune status. Global sensitivity methods provide the de-correlated outcome sensitivities to each source of within-host heterogeneity, including the dynamic progression of sensitivities at 12, 24, 36, and 48 hours post infection. The results reveal a dynamic rank-ordering of the drivers of outcome sensitivity in early infection, providing insights into the dramatic population-scale outcome diversity during the COVID-19 pandemic. While we focus on SARS-CoV-2, the model and methods are applicable to any inhaled virus in the immediate 48 hours post infection.
- organism: human
- assay: spatial transcriptomics
- research focus: cell type annotation
- approach: statistical model
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Spatially distributed infection increases viral load in a computational model of SARS-CoV-2 lung infection
M. E. Moses, S. Hofmeyr, … S. Forrest·bioRxiv·May 19, 2021
- Modelling the within-host spread of SARS-CoV-2 infection, and the subsequent immune response, using a hybrid, multiscale, individual-based model. Part I: Macrophages.
Christopher Rowlatt, Mark A. J. Chaplain, … Ruth Bowness·bioRxiv·May 6, 2022
- Self-inhibiting percolation and viral spreading in epithelial tissue
Xiaochan Xu, Bjarke Frost Nielsen, Kim Sneppen·eLifePeer-reviewed·Jan 24, 2024
- Human nasal and lung tissues infected ex vivo with SARS-CoV-2 provide insights into differential tissue-specific and virus-specific innate immune responses in the upper and lower respiratory tract
O. Alfi, A. Yakirevich, … D. G. Wolf·bioRxiv·Mar 8, 2021
- Disparate temperature-dependent virus - host dynamics for SARS-CoV-2 and SARS-CoV in the human respiratory epithelium
P. V'kovski, M. Gultom, … R. Dijkman·bioRxiv·Apr 27, 2020
- In Silico Modeling of Virus Particle Propagation and Infectivity along the Respiratory Tract: A Case Study for SARS-COV-2
Dixon Vimalajeewa, Sasitharan Balasubramaniam, … Gerald Barry·bioRxiv·Aug 20, 2020