Stochastic failure of cell infection post viral entry: Implications for infection outcomes and antiviral therapy
Christian Quirouette, Daniel Cresta, Jizhou Li, Kathleen P. Wilkie,, Haozhao Liang, Catherine A.A. Beauchemin

TL;DR
This paper introduces a stochastic model of viral infection that accounts for failure after viral entry, providing insights into infection extinction probabilities and implications for antiviral therapy strategies.
Contribution
It develops a new stochastic model incorporating post-entry failure probability and analyzes its impact on infection outcomes and antiviral efficacy.
Findings
Prophylactic antivirals reducing entry success increase extinction probability.
Infection extinction likelihood is unaffected by burst size distribution when virus release is a single burst.
The model shows the importance of post-entry failure in infection dynamics and therapy design.
Abstract
A virus infection can be initiated with very few or even a single infectious virion, and as such can become extinct, i.e. stochastically fail to take hold or spread significantly. There are many ways that a fully competent infectious virion, having successfully entered a cell, can fail to cause a productive infection, i.e. one that yields infectious virus progeny. Though many discrete, stochastic mathematical models (DSMs) have been developed and used to estimate a virus infection's extinction probability, these typically neglect infection failure post viral entry. The DSM presented herein introduces parameter which corresponds to the probability that a virion's entry into a cell will result in a productive cell infection. We derive an expression for the likelihood of infection extinction in this new DSM, and find that prophylactic therapy with an antiviral acting to…
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Taxonomy
TopicsEvolution and Genetic Dynamics · SARS-CoV-2 and COVID-19 Research · COVID-19 epidemiological studies
