论文标题
互动热点的动力学 - 我
Dynamics of Interacting Hotspots -- I
论文作者
论文摘要
Covid-19的全球传播呼吁快速发展新的建模策略，以估计其前所未有的蔓延。在这里，我们通过随机交换城市之间的感染种群的随机交换，以在模型状态下的Epcentres相互作用网络中研究动态，从而基于具有随机疾病的基本SIR方程的模型。尽管每种随机交换都可以保守人口，但该疾病将全球系统推向了新的动态均衡路线。在控制交换部分的范围后，我们表明可以控制扩散中的异质性以及相互作用的热点之间的合作性。在德国联邦州，受感染人群的集体时间演变的数据验证了该模型的定性特征。
The worldwide spread of COVID-19 has called for fast advancement of new modelling strategies to estimate its unprecedented spread. Here, we introduce a model based on the fundamental SIR equations with a stochastic disorder by a random exchange of infected populations between cities to study dynamics in an interacting network of epicentres in a model state. Although each stochastic exchange conserves populations pair-wise, the disorder drives the global system towards newer routes to dynamic equilibrium. Upon controlling the range of the exchange fraction, we show that it is possible to control the heterogeneity in the spread and the co-operativity among the interacting hotspots. Data of collective temporal evolution of the infected populations in federal states of Germany validate the qualitative features of the model.
