Optimal Curing Strategy for Competing Epidemics Spreading over Complex Networks
arXiv:2011.14262
Abstract
Optimal curing strategy of suppressing competing epidemics spreading over complex networks is a critical issue. In this paper, we first establish a framework to capture the coupling between two epidemics, and then analyze the system's equilibrium states by categorizing them into three classes, and deriving their stability conditions. The designed curing strategy globally optimizes the trade-off between the curing cost and the severity of epidemics in the network. In addition, we provide structural results on the predictability of epidemic spreading by showing the existence and uniqueness of the solution. We also demonstrate the robustness of curing strategy by showing the continuity of epidemic severity with respect to the applied curing effort. A gradient descent algorithm based on a fixed-point iterative scheme is proposed to find the optimal curing strategy. Depending on the system parameters, the curing strategy can lead to switching between equilibria of the epidemic network as the control cost varies. Finally, we use case studies to corroborate and illustrate the obtained theoretical results.
arXiv comment15 pages
References in corpus (13)
- Emergence of scaling in random networks
- Epidemic spreading in scale-free networks
- Epidemic processes in complex networks
- The spread of epidemic disease on networks
- Immunization of complex networks
- Dynamical interplay between awareness and epidemic spreading in multiplex networks
- Dynamics of Rumor Spreading in Complex Networks
- Epidemic dynamics on an adaptive network
- Epidemic spreading on interconnected networks
- Optimal Resource Allocation for Network Protection Against Spreading Processes
- Competing epidemics on complex networks
- Epidemic spread in weighted scale-free networks
- Optimal Secure Multi-Layer IoT Network Design