  The SIR model is used extensively in the field of epidemiology, in
particular, for the analysis of communal diseases. One problem with SIR and
other existing models is that they are tailored to random or Erdos type
networks since they do not consider the varying probabilities of infection or
immunity per node. In this paper, we present the application and the simulation
results of the pSEIRS model that takes into account the probabilities, and is
thus suitable for more realistic scale free networks. In the pSEIRS model, the
death rate and the excess death rate are constant for infective nodes. Latent
and immune periods are assumed to be constant and the infection rate is assumed
to be proportional to I (t) N(t), where N (t) is the size of the total
population and I(t) is the size of the infected population. A node recovers
from an infection temporarily with a probability p and dies from the infection
with probability (1-p).
