Protection Strategy against an Epidemic Disease on Edge-Weighted Graphs Applied to a COVID-19 Case

Abstract

Among the diverse and important applications that networks currently have is the modeling of infectious diseases. Immunization, or the process of protecting nodes in the network, plays a key role in stopping diseases from spreading. Hence the importance of having tools or strategies that allow the solving of this challenge. In this paper, we evaluate the effectiveness of the DIL-W${}^{\alpha }$ ranking in immunizing nodes in an edge-weighted network with 3866 nodes and 6,841,470 edges. The network is obtained from a real database and the spread of COVID-19 was modeled with the classic SIR model. We apply the protection to the network, according to the importance ranking list produced by DIL-W${}^{\alpha }$, considering different protection budgets. Furthermore, we consider three different values for $\alpha$; in this way, we compare how the protection performs according to the value of $\alpha$.