初始状态对传染病传播过程影响的仿真研究

Simulation Study on the Influence of Initial State on the Transmission Process of Infectious Diseases

佟昕媛 曹宇 魏海平

Xinyuan Tong Yu Cao Haiping Wei

辽宁石油化工大学 人工智能与软件学院，辽宁 抚顺 113001

School of Artificial Intelligence and Software，Liaoning Petrochemical University，Fushun Liaoning 113001，China

长期以来，研究人员大都通过对染病节点在复杂网络中的传播过程进行分析，进而达到预测和防治传染病传播的目的。将SEIR传播动力学模型推广至无向无权大型小世界网络中，并为节点间赋予权值作为感染能力，选用2种初始节点选择方法进行多次仿真实验；在传统的通过感染人数、感染阈值判断传播影响的基础上，又增加了感染概率、峰值、拐点时间的具体值，更加全面地分析了初始节点选择对传播过程的影响。结果表明，初始节点的度与介数越大，其传播的规模越大，传播速度越快，达到平衡时间越短。研究内容可为预防和控制传染病传播提供一定的参考价值。

For a long time, researchers mostly analyze the transmission process of infected nodes in complex networks to get the target of forecasting and arresting the extend of the infectious diseases. In this article, the SEIR propagation dynamics model was extended to the undirected and powerless large small world network, and the weights between nodes were given as infection ability. Two initial node selection methods were selected to carry out multiple simulation experiments. Based on the traditional method of judging the impact of transmission by the number of infected people and infection threshold, the specific values of infection probability, peak value and inflection point time were added to analyze the impact of initial node selection on transmission process more comprehensively. The compared experimental results show that the initial node which the degree is larger and the betweenness is larger, the larger the propagation scale, the faster the propagation speed and the shorter the equilibrium time. This study provides some reference value for guard against and control of the extend of infectious diseases.

辽宁省教育科学“十三五”规划立项重点课题项目(JG18DA013);辽宁省重点研究开发项目(2020JH2/10300040);辽宁省教育厅一般项目(L2020031)

10.12422/j.issn.1672-6952.2023.02.015