Transmission of SARS-CoV-2 on Barabási–Albert network under constant and variable rates of infection

The SARS-CoV-2 has been affecting all countries since its outbreak in 2019 from China. Since then the epidemiological models are being used to predict the dynamics of the disease. These models are based on random diffusion of the disease and hence ignore the social interactions that naturally exist in a society. To take into account the human interactions, it is novel to consider the network approach. In this paper, we give numerical simulations of the Susceptible–Exposed–Infected–Recovered model on the Barabási–Albert network to analyze the dynamics of the SARS-CoV-2 in Pakistan under constant and variable rates of infection. We also show a day-by-day transmission of the disease in the network under both the rates and observe that the disease diffuses slowly with variable rate of infection as compared to constant rate. It is figured out that we can efficiently control the transmission if we keep it from entering the nodes with high degree of connections.