论文标题
基于程度的SIR模型的近似值和触点示意图和分离
A Degree Based Approximation of an SIR Model with Contact Tracing and Isolation
论文作者
论文摘要
在本文中，我们研究了一种易感感染感染恢复的（SIR）模型，该模型与无症状患者，接触跟踪和在配置网络上的隔离。使用基于学位的近似，我们为该模型得出一个微分方程的系统。该系统无法通过分析解决。我们为模型提供了早期分析。早期分析产生流行阈值。在阈值的一侧，疾病迅速死亡。另一方面，大部分人口被感染。阈值仅取决于疾病的参数，网络的平均接入度以及无症状患者的比例。阈值不取决于接触跟踪和隔离策略的参数。我们提出了一个近似分析，大大降低了计算复杂性。从近似值得出的非线性系统几乎不是线性的。我们为该系统提供了稳定性分析。我们在五个现实世界网络上使用接触跟踪和隔离来模拟SIR模型。模拟结果表明，接触跟踪和隔离对于包含流行病很有用。
In this paper we study a susceptible infectious recovered (SIR) model with asymptomatic patients, contact tracing and isolation on a configuration network. Using degree based approximation, we derive a system of differential equations for this model. This system can not be solved analytically. We present an early-time analysis for the model. The early-time analysis produces an epidemic threshold. On one side of the threshold, the disease dies out quickly. On the other side, a significant fraction of the population are infected. The threshold only depends on the parameters of the disease, the mean access degree of the network, and the fraction of asymptomatic patients. The threshold does not depend on the parameter of contact tracing and isolation policy. We present an approximate analysis which greatly reduces computational complexity. The nonlinear system derived from the approximation is not almost linear. We present a stability analysis for this system. We simulate the SIR model with contact tracing and isolation on five real-world networks. Simulation results show that contact tracing and isolation are useful to contain epidemics.
