Van Mieghem Piet
Delft University of Technology, Faculty of Electrical Engineering, Mathematics and Computer Science, P.O. Box 5031, 2600 GA Delft, The Netherlands.
Phys Rev E. 2020 Mar;101(3-1):032303. doi: 10.1103/PhysRevE.101.032303.
The ɛ-susceptible-infected-susceptible (SIS) epidemic model on a graph adds an independent, Poisson self-infection process with rate ɛ to the "classical" Markovian SIS process. The steady state in the classical SIS process (with ɛ=0) on any finite graph is the absorbing or overall-healthy state, in which the virus is eradicated from the network. We report that there always exists a phase transition around τ_{c}^{ɛ}=O(ɛ^{-1/N-1}) in the ɛ-SIS process on the complete graph K_{N} with N nodes, above which the effective infection rate τ>τ_{c}^{ɛ} causes the average steady-state fraction of infected nodes to approach that of the mean-field approximation, no matter how small, but not zero, the self-infection rate ɛ is. For τ<τ_{c}^{ɛ} and small ɛ, the network is almost overall healthy. The observation was found by mathematical analysis on the complete graph K_{N}, but we claim that the phase transition of explosive type may also occur in any other finite graph. We thus conclude that the overall-healthy state of the classical Markovian SIS model is unstable in the ɛ-SIS process and, hence, unlikely to exist in reality, where "background" infection ɛ>0 is imminent.
图上的易感染-感染-易感染(SIS)流行病模型在“经典”马尔可夫SIS过程中添加了一个速率为ɛ的独立泊松自感染过程。在任何有限图上的经典SIS过程(ɛ = 0)中的稳态是吸收态或整体健康态,即病毒从网络中根除。我们报告,在具有N个节点的完全图(K_N)上的ɛ-SIS过程中,总是存在一个围绕(\tau_{c}^{ɛ}=O(ɛ^{-(1/N + 1)}))的相变,高于此相变,有效感染率(\tau>\tau_{c}^{ɛ})会使感染节点的平均稳态比例接近平均场近似值,无论自感染率ɛ多么小但不为零。对于(\tau<\tau_{c}^{ɛ})且ɛ较小时,网络几乎整体健康。这一观察结果是通过对完全图(K_N)的数学分析得出的,但我们声称这种爆发型相变也可能发生在任何其他有限图中。因此,我们得出结论,经典马尔可夫SIS模型的整体健康态在ɛ-SIS过程中是不稳定的,因此在现实中不太可能存在,因为现实中“背景”感染ɛ>0是不可避免的。