Inefficient epidemic spreading in scale-free networks.
This paper describes a new approach to the modeling of epidemic dynamics with complex networks. The infection spreading considers the links of each ill node and the probability to infect healthy nodes. Moreover, a fitness parameter is used for each node of a network to simulate the individual reaction against an infectious process. The dynamics of infection has been evaluated on different kinds of complex networks, allowing to conclude that minimal conditions (in terms of infection probability and individual fitness) are required for infection spreading. According to the results obtained during simulations, we claim that the proposed model can be considered a good candidate to study viral spreading in social networks or in those biological systems with a high individual variability in reaction to infections.