Epidemic Spreading with Co-infection on Long-Range Random Networks

arXiv:2508.08294v1 Announce Type: new
Abstract: We study a discrete-time co-infection epidemic model on spatial networks incorporating both random and long-range interactions. Using numerical analysis, we investigate how the co-infection recovery rate ($mu$), the interaction distance decay exponent ($alpha$), and network connectivity parameters affect epidemic persistence. Our results show that lower values of ($mu$) facilitate long-term survival, and that the presence of long-range connections ($alpha > 0$) robustly enhances persistence, often outweighing the effects of co-infection dynamics and local connectivity. These findings highlight nontrivial threshold behavior and the critical role of long-range structure in heterogeneous, nonlocal epidemic systems.