Estudo da dinâmica de epidemias em redes aleatórias

Abstract

We present a deterministic model SEIR (susceptible, exposed, infected, recovered) to the dynamics of epidemics of influenza, we calculate its equilibrium points and the basic reproductive number (R0). The results of simulations of the dynamics of contagion are shown, in a population subdivided in demes using three types of complex networks which have the character of “small world” (relatively short distances between the nodes of the network and high degree of coupling) and “scale free” (presence of nodes with high connectivity) and compare with the dynamics of contagion observed in the regular network. We observed that the disease spread faster in scale-free network compared to other two, in the small world network as the probability of reconnection is incremented the speed of spreading of the disease is also increased and on the regular network the disease spread more slowly. For the three types of network, there were experiments with different percentages of vaccinated individuals, using two techniques for selecting the sample of individuals, random selection of individuals and conglomerates. The results show that if the rate at which an individual recovered becomes exposed (s ) is 0.4 and with a 60% of vaccinees at random we get a persistence of the disease almost zero, while as with vaccination of individuals by conglomerates that persistence is close to 80%. When we have s = 1, the random vaccination of individuals also results more effective because with 80% of vaccinated individualsthe persistent is almost zero, while for clusters with vaccination even with 99% of vaccinees the disease still persists. Here, we can conclude that vaccination of individuals in a random way result be more effective than the vaccination done in groups.