Cui Peng-Bi, Colaiori Francesca, Castellano Claudio
Istituto dei Sistemi Complessi (ISC-CNR), UOS Sapienza, Piazzale Aldo Moro 2, 00185 Roma, Italy.
Web Sciences Center, University of Electronic Science and Technology of China, Chengdu 611731, China.
Phys Rev E. 2017 Aug;96(2-1):022301. doi: 10.1103/PhysRevE.96.022301. Epub 2017 Aug 1.
The spread of an infectious disease can, in some cases, promote the propagation of other pathogens favoring violent outbreaks, which cause a discontinuous transition to an endemic state. The topology of the contact network plays a crucial role in these cooperative dynamics. We consider a susceptible-infected-removed-type model with two mutually cooperative pathogens: An individual already infected with one disease has an increased probability of getting infected by the other. We present a heterogeneous mean-field theoretical approach to the coinfection dynamics on generic uncorrelated power-law degree-distributed networks and validate its results by means of numerical simulations. We show that, when the second moment of the degree distribution is finite, the epidemic transition is continuous for low cooperativity, while it is discontinuous when cooperativity is sufficiently high. For scale-free networks, i.e., topologies with diverging second moment, the transition is instead always continuous. In this way we clarify the effect of heterogeneity and system size on the nature of the transition, and we validate the physical interpretation about the origin of the discontinuity.
在某些情况下,传染病的传播会促进其他病原体的传播,从而引发剧烈的疫情爆发,导致向地方病状态的不连续转变。接触网络的拓扑结构在这些协同动态中起着关键作用。我们考虑一个具有两种相互协同病原体的易感-感染-移除型模型:已经感染一种疾病的个体感染另一种疾病的概率会增加。我们针对一般的无关联幂律度分布网络上的共感染动态提出了一种非均匀平均场理论方法,并通过数值模拟验证了其结果。我们表明,当度分布的二阶矩有限时,对于低协同性,疫情转变是连续的,而当协同性足够高时则是不连续的。对于无标度网络,即二阶矩发散的拓扑结构,转变反而总是连续的。通过这种方式,我们阐明了异质性和系统规模对转变性质的影响,并验证了关于不连续性起源的物理解释。