Epidemiological model based on networks with non-local coupling

Epidemics result in loss of human lives and have a significative socioeconomic impact. In this context, epidemiological models play a crucial role in prevention and control of spread diseases. The main goal of the present work is to analyze the dispersal of an illness in a complex network of coupled sites as a function of the model parameters. Our results indicate that non-local connections lead to a quicker epidemic spread, while lower interaction between sites contributes to a slower spread. Parameters such as infection rate and initial susceptible individuals influence the epidemic dispersion, while the recovery rate and initial infected individuals at the reference site have limited impact on the disease evolution in the network.