Mechanisms to decrease the diseases spreading on generalized scale-free networks

In this work, an epidemiological model is constructed based on a target problem that consists of a chemical reaction on a lattice. We choose the generalized scale-free network to be the underlying lattice. Susceptible individuals become the targets of random walkers (infectious individuals) that are moving over the network. The time behavior of the susceptible individuals' survival is analyzed using parameters like the connectivity γ of the network and the minimum (K_min) and maximum (K_max) allowed degrees, which control the influence of social distancing and isolation or spatial restrictions. In all cases, we found power-law behaviors, whose exponents are strongly influenced by the parameter γ and to a lesser extent by K_max and K_min, in this order. The number of infected individuals diminished more efficiently by changing the parameter γ, which controls the topology of the scale-free networks. A similar efficiency is also reached by varying K_max to extremely low values, i.e., the number of contacts of each individual is drastically diminished.