Max Planck Institute for the Physics of Complex Systems, Dresden, Germany and JSC, FZ Jülich, D-52425 Jülich, Germany.
Robert Koch Institute, 13353 Berlin, Germany and Max Planck Institute for the Physics of Complex Systems, Dresden, Germany.
Phys Rev E. 2016 Apr;93:042316. doi: 10.1103/PhysRevE.93.042316. Epub 2016 Apr 26.
We study the spreading of two mutually cooperative diseases on different network topologies, and with two microscopic realizations, both of which are stochastic versions of a susceptible-infected-removed type model studied by us recently in mean field approximation. There it had been found that cooperativity can lead to first order transitions from spreading to extinction. However, due to the rapid mixing implied by the mean field assumption, first order transitions required nonzero initial densities of sick individuals. For the stochastic model studied here the results depend strongly on the underlying network. First order transitions are found when there are few short but many long loops: (i) No first order transitions exist on trees and on 2-d lattices with local contacts. (ii) They do exist on Erdős-Rényi (ER) networks, on d-dimensional lattices with d≥4, and on 2-d lattices with sufficiently long-ranged contacts. (iii) On 3-d lattices with local contacts the results depend on the microscopic details of the implementation. (iv) While single infected seeds can always lead to infinite epidemics on regular lattices, on ER networks one sometimes needs finite initial densities of infected nodes. (v) In all cases the first order transitions are actually "hybrid"; i.e., they display also power law scaling usually associated with second order transitions. On regular lattices, our model can also be interpreted as the growth of an interface due to cooperative attachment of two species of particles. Critically pinned interfaces in this model seem to be in different universality classes than standard critically pinned interfaces in models with forbidden overhangs. Finally, the detailed results mentioned above hold only when both diseases propagate along the same network of links. If they use different links, results can be rather different in detail, but are similar overall.
我们研究了两种相互合作的疾病在不同网络拓扑结构上的传播,并采用了两种微观实现方式,这两种方式都是我们最近在平均场近似下研究的易感染-感染-清除型模型的随机版本。在那里,我们发现合作可以导致从传播到灭绝的一级相变。然而,由于平均场假设所暗示的快速混合,一级相变需要非零的初始患病个体密度。对于这里研究的随机模型,结果强烈依赖于基础网络。当存在少量但许多长回路时,会发现一级相变:(i)在树和局部接触的二维格子上不存在一级相变。(ii)在 Erdős-Rényi(ER)网络、d≥4 维的晶格和具有足够长程接触的二维格子上存在一级相变。(iii)在局部接触的三维晶格上,结果取决于微观实现的细节。(iv)虽然在规则晶格上,单个感染的种子总能导致无限的流行病,但在 ER 网络上,有时需要感染节点的有限初始密度。(v)在所有情况下,一级相变实际上是“混合的”;即,它们也显示了通常与二级相变相关的幂律标度。在规则晶格上,我们的模型也可以被解释为由于两种粒子的合作附着而导致的界面生长。在这个模型中,临界钉扎的界面似乎与具有禁止悬垂的模型中的标准临界钉扎界面处于不同的通用类别。最后,上面提到的详细结果仅在两种疾病沿着相同的链路网络传播时才成立。如果它们使用不同的链路,结果在细节上可能会有很大的不同,但总体上是相似的。