Author(s)

James K. Peterson^1*, Alison M. Kesson^2,3, Nicholas J. C. King⁴

¹Department of Mathematical and Biological Sciences, Clemson University, Clemson, SC, USA.
²Department of Infectious Diseases and Microbiology, The Children’s Hospital, Sydney, Australia.
³Discipline of Pediatrics and Child Health, The Marie Bashir Institute for Emerging Infectious Diseases and Biosecurity, University of Sydney, Sydney, Australia.
⁴Discipline of Pathology, University of Sydney, Sydney, Australia.

Simulation code for a model of the adaptive immune response seen in flavivirus infections is used to explain the immunopathological consequences seen in West Nile Virus virus (WNV) infections. We use a model that specifically handles the differences in how the virus infects resting cells, the G0 state, versus dividing cells, the G1 state, which includes vastly increased MHC-I upregulation for resting cells over dividing cells. The simulation suggests how the infection progresses in a one host model and the results shed insight into the unusual survival curve data obtained for this infection: there is an increase in health even though viral load has increased.

Auto Immune Responses, West Nile Virus, Host Survival Models, MHC-I Upregulation, IFN-γ Upregulation, Free Antigen Levels

Peterson, J. , Kesson, A. and King, N. (2016) Using a Collateral Damage Model to Explain Survival Data in West Nile Virus Infections. Advances in Microbiology, 6, 251-262. doi: 10.4236/aim.2016.64025.