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A virus infection can be initiated with very few or even a single infectiousvirion, and as such can become extinct, i.e. stochastically fail to take holdor spread significantly. There are many ways that a fully competent infectiousvirion, having successfully entered a cell, can fail to cause a productiveinfection, i.e. one that yields infectious virus progeny. Though many discrete,stochastic mathematical models (DSMs) have been developed and used to estimatea virus infection's extinction probability, these typically neglect infectionfailure post viral entry. The DSM presented herein introduces parameter$\gamma\in(0,1]$ which corresponds to the probability that a virion's entryinto a cell will result in a productive cell infection. We derive an expressionfor the likelihood of infection extinction in this new DSM, and find thatprophylactic therapy with an antiviral acting to reduce $\gamma$ is best atincreasing an infection's extinction probability, compared to antivirals actingon the rates of virus production or virus entry into cells. Using the DSM, weinvestigate the difference in the fraction of cells consumed by so-calledextinct versus established virus infections, and find that this distinctionbecomes biologically meaningless as the probability of extinction approaches100%. We show that infections wherein virus is release by an infected cell as asingle burst, rather than at a constant rate over the cell's infectiouslifespan, has the same probability of infection extinction, despite previousclaims to this effect [Pearson 2011, doi:10.1371/journal.pcbi.1001058].Instead, extending previous work by others [Yan 2016,doi:10.1007/s00285-015-0961-5], we show how the assumed distribution for thestochastic virus burst size, affects the extinction probability and associatedcritical antiviral efficacy.

Stochastic failure of cell infection post viral entry: Implications for infection outcomes and antiviral therapy