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. 2011 May 14;4:1798–1807. doi: 10.1016/j.procs.2011.04.195

A Simulation Framework to Investigate in vitro Viral Infection Dynamics

Armand Bankhead III b,1, Emiliano Mancini a,1, Amy C Sims c, Ralph S Baric c, Shannon McWeeney b, Peter MA Sloot a
PMCID: PMC7129957  PMID: 32288900

Abstract

Virus infection is a complex biological phenomenon for which in vitro experiments provide a uniquely concise view where data is often obtained from a single population of cells, under controlled environmental conditions. Nonetheless, data interpretation and real understanding of viral dynamics is still hampered by the sheer complexity of the various intertwined spatio-temporal processes. In this paper we present a tool to address these issues: a cellular automata model describing critical aspects of in vitro viral infections taking into account spatial characteristics of virus spreading within a culture well. The aim of the model is to understand the key mechanisms of SARS-CoV infection dynamics during the first 24 hours post infection. We interrogate the model using a Latin Hypercube sensitivity analysis to identify which mechanisms are critical to the observed infection of host cells and the release of measured virus particles.

Keywords: Cellular automata, infection dynamics, SARS, simulation ;

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