基于SI1SI2R模型的异质群体重复感染的传染病建模与仿真

摘要/Abstract

摘要： 具有重复感染可能性的传染病由于不受抗体或疫苗等手段的阻碍，其传播范围会比普通传染病更加广泛，严重危害人类的身心健康，影响社会的和谐稳定，有必要对其传播规律进行探究，以便于更有针对性地制定应对策略。基于经典的传染病模型，本文构建考虑了传染病重复感染特征的SI1SI2R模型，定义异质性个体之间的交互及传播规则，并利用ABM仿真建模的方法探究具有重复性感染特征的传染病在异质性群体间的传播规律。仿真实验结果表明，此类传染病感染范围会随二次感染率的提升而增加，而异质性传播群体的组成不仅会影响感染人数的比例，还会影响其到达峰值的时间。因此，不仅要减小此类疾病反复感染的可能，还要根据传播群体的异质性提出更有效率的管理方案。

关键词: 传染病, 仿真, ABM, 传播规律

Abstract: Because the infectious diseases with the possibility of repeated infection are not hindered by antibodies or vaccines, their spread ranges are more extensive than ordinary infectious diseases, which seriously endangers human physical and mental health and affects social harmony and stability. It is necessary to explore the transmission law of infectious diseases, so as to formulate more targeted coping strategies. Based on the classical infectious disease model, SI1SI2R model of considering the characteristics of repeated infection of infectious diseases is constructed, and the interaction and transmission rules between heterogeneous individuals are defined. The transmission law of infectious diseases with repetitive infection characteristics among heterogeneous groups is explored by using ABM simulation modeling method. The simulation results show that the infection range of this kind of infectious diseases increases with the increase of secondary infection rate, and the composition of heterogeneous transmission groups not only affects the proportion of infected people, but also affects the time to reach the peak. Therefore, it is not only necessary to reduce the possibility of repeated infection of such diseases, but also necessary to put forward more efficient management schemes according to the heterogeneity of transmission groups.

Key words: infectious disease, simulation, ABM, transmission law

孙璐, 薛晓斐, 程妞妞. 基于SI1SI2R模型的异质群体重复感染的传染病建模与仿真[J]. 计算机与现代化, 2021, 0(05): 98-104.

SUN Lu, XUE Xiao-fei, CHENG Niu-niu. Modeling and Simulation of Infectious Diseases in Heterogeneous Population with Repeated Infection Based on SI1SI2R Model[J]. Computer and Modernization, 2021, 0(05): 98-104.

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