Diseases on complex networks. Modeling from a database and a protection strategy proposal
arXiv:2107.09670
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 work, we evaluate the effectiveness of the DIL-W^α ranking in immunizing nodes in an edge-weighted network. 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^α.
References in corpus (7)
- Cooperative Game Theory Approaches for Network Partitioning
- Efficient Immunization Strategies for Computer Networks and Populations
- Reaction-diffusion processes and metapopulation models in heterogeneous networks
- Power-law Strength-Degree Correlation From a Resource-Allocation Dynamics on Weighted Networks
- Immunization of Real Complex Communication Networks
- Spreading of infections on random graphs: A percolation-type model for COVID-19
- Group based Centrality for Immunization of Complex Networks