| Popis: |
The main goal of this work is to reformulate the compartmental and deterministic global SIR Kermack-McKendrick model in terms of stochastic and individual-based techniques. Specifically, the novel model proposed is based on the use of a probabilistic cellular automaton. Specific local transition functionsendowed with appropriate epidemiological coefficients are considered with the aim to replicate the simulation results obtained from the global and continuous approach. Moreover, this new model exhibits important improvements with respect to the original Kermack-McKendrick model: different contact topologies can be considered (not only complete networks but also small-world networks and scale-free networks) and also specific and differentiating characteristics of the devices (resistance to infection, number of adjacent infectious nodes, detection and removal coefficients, etc.) and the specimen of malware (virulence) are taken into account. A comparison between both models is introduced by showing that scale-free networks accelerate the propagation process. |
Full Text from ScienceDirect