Numerical simulations with mitigation strategies on Barabási-Albert network for the spread of coronavirus in Pakistan

Abstract

Since its emergence in China in 2019, the coronavirus has exerted its impact on every nation. Throughout this period, epidemiological models have been employed to anticipate the disease's patterns. These models rely on the random diffusion of the virus, overlooking the inherent social interactions within communities. A pioneering approach involves incorporating the concept of networks to account for these human interactions. The present study presents visual depictions of numerical simulations utilizing the Susceptible-Infected-Recovered model on the Barabasi-Albert network. This enables an analysis of coronavirus dynamics in Pakistan while considering diverse mitigation strategies. The findings underscore that effective infection management involves preventing its spread into central hubs-nodes with extensive connections-and significantly curtailing social interactions within society.