  Much of the work on modeling the spread of viral infections utilized partial
differential equa- tions. Traveling-wave solutions to these PDEs are typically
concentrated on velocities and their dependence on the various parameters. Most
of the investigations into the dynamical interaction of virus and defective
interfering particles (DIP), which are incomplete forms of the virus that
replicate through co-infection, have followed the same lines. In this work we
present an agent based model of viral infection with consideration of DIP and
the negative feedback loop introduced by interferon production as part of the
host innate immune response. The model is based high resolution microscopic
images of plaques of dead cells we took from mammalian cells infected with
Sendai virus with low and high DIP. In order to investigate the effects of the
discrete stochastic microscopic mechanisms, which are responsible for virus
spreading, have on the macroscopic growth of viral plaques, we generate an
agent-based model of viral infection. The two main aims of this work are to (i)
investigate the effects of discrete microscopic randomness on the macroscopic
growth of viral plaques; and (ii) examine the dynamic interactions between the
full length virus, DIP and interferon, and interpret what may be the function
of DIP. We find that we can explain the qualitative differences between our
stochastic model and deterministic models in terms of the fractal geometry of
the resulting plaques, and that DIP have a delaying effect while the
interaction between interferon and DIP has a slowing effect on the growth of
viral plaques, potentially contributing to viral latency.
