A stochastic model for virus growth in a cell population

TL;DR

This paper introduces a stochastic model for virus growth in cell populations, analyzing how different spreading strategies affect survival, and finds that viruses survive best without harming host cells, aligning with real-world observations.

Contribution

The paper presents a new stochastic model combining two virus spreading mechanisms and analyzes the optimal survival strategy using Markov process theory.

Findings

Optimal virus survival occurs when the virus does not affect host cell life-cycle.

The model aligns with experimental data on real viruses.

Analysis shows the importance of spreading strategy on virus persistence.

Abstract

A stochastic model for the growth of a virus in a cell population is introduced. The virus has two ways of spreading: either by allowing its host cell to live on and duplicate, or else by multiplying in large numbers within the host cell such that the host cell finally bursts and the viruses then have the chance to enter new uninfected host cells. The model, and in particular the probability of the virus population surviving, is analyzed using the theory of Markov processes together with a coupling argument. Our analysis shows that the optimal strategy of the virus (in terms of survival) is obtained when the virus has no effect on the host cell's life-cycle, in agreement with experimental data about real viruses.