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Much of the work on modeling the spread of viral infections utilized partialdifferential equa- tions. Traveling-wave solutions to these PDEs are typicallyconcentrated on velocities and their dependence on the various parameters. Mostof the investigations into the dynamical interaction of virus and defectiveinterfering particles (DIP), which are incomplete forms of the virus thatreplicate through co-infection, have followed the same lines. In this work wepresent an agent based model of viral infection with consideration of DIP andthe negative feedback loop introduced by interferon production as part of thehost innate immune response. The model is based high resolution microscopicimages of plaques of dead cells we took from mammalian cells infected withSendai virus with low and high DIP. In order to investigate the effects of thediscrete stochastic microscopic mechanisms, which are responsible for virusspreading, have on the macroscopic growth of viral plaques, we generate anagent-based model of viral infection. The two main aims of this work are to (i)investigate the effects of discrete microscopic randomness on the macroscopicgrowth of viral plaques; and (ii) examine the dynamic interactions between thefull length virus, DIP and interferon, and interpret what may be the functionof DIP. We find that we can explain the qualitative differences between ourstochastic model and deterministic models in terms of the fractal geometry ofthe resulting plaques, and that DIP have a delaying effect while theinteraction between interferon and DIP has a slowing effect on the growth ofviral plaques, potentially contributing to viral latency.

Stochastic model of virus and defective interfering particle spread across mammalian cells with immune response