论文标题
社会疏远对于传染性疾病传播至关重要吗？ SEIR模型和基于Gompertz法律的细胞自动机
Does social distancing matter for infectious disease propagation? A SEIR model and Gompertz law based cellular automaton
论文作者
论文摘要
在本文中，我们提出了在平方晶格上定义的随机同步细胞自动机。自动机规则基于SEIR（易感$ \ to $ to $ \ to $ to $感染的$ \ to $ feccousned）模型，其模型从现实世界中的人类死亡率和SARS-COV-2疾病的特征中收集的概率参数。通过计算机模拟，我们展示了邻里半径对人造人群中感染和已故药物数量的影响。邻里半径的增加有利于流行病的传播。但是，对于暴露剂的各种相互作用（既没有疾病的症状也没有通过适当的测试来诊断），即使是被感染剂的隔离也无法阻止成功的疾病传播。这支持针对疾病的积极测试是防止SARS-COV-2样疾病传播中大量感染峰的有用策略之一。
In this paper, we present stochastic synchronous cellular automaton defined on a square lattice. The automaton rules are based on the SEIR (susceptible $\to$ exposed $\to$ infected $\to$ recovered) model with probabilistic parameters gathered from real-world data on human mortality and the characteristics of the SARS-CoV-2 disease. With computer simulations, we show the influence of the radius of the neighborhood on the number of infected and deceased agents in the artificial population. The increase in the radius of the neighborhood favors the spread of the epidemic. However, for a large range of interactions of exposed agents (who neither have symptoms of the disease nor have been diagnosed by appropriate tests), even isolation of infected agents cannot prevent successful disease propagation. This supports aggressive testing against disease as one of the useful strategies to prevent large peaks of infection in the spread of SARS-CoV-2-like disease.
