病毒传播变异与人群交叉活动的相互影响及扩散模型研究

doi:10.16182/j.issn1004731x.joss.23-0478

摘要/Abstract

摘要：

针对当前人际传染病毒高发态势，综合考虑病毒传播变异的随机特征和人群交叉活动之间的相互影响，提出并设计了多智能体模拟仿真推演模型。将病毒个体的外在致病性、传染性特征和人群个体的外在活动、免疫特征进行量化，将病毒个体与人群个体之间的相互依存及对抗过程进行建模，通过模型推演大量病毒个体和人群个体的发展趋势和统计特征。通过实验分析揭示了单个病毒变异方向的随机性不影响病毒群体变异发展方向的确定性：即病毒群体的致病性强度不断降低直到稳定在低值区间内，病毒群体的传染性强度不断升高，直到稳定在较高的数值区间内。给出了影响病毒传播变异过程的关键外在参数，可为高致病性病毒早期防控提供政策建议。

关键词: 病毒传播模型, 多智能体仿真, 预防和控制策略, 流行病病毒特征发展趋势, 遗传变异

Abstract:

In view of the current high incidence of human-to-human infectious viruses, a multi-agent simulation and deduction model was proposed and designed based on the random characteristics of virus transmission variation and the influence of population crossover activity. The external pathogenicity and infectious characteristics of the virus and the external activities and immune characteristics of the human were quantified, and the interdependence and confrontation process between the virus and the human were modeled. The development trends and statistical characteristics of a large number of viruses and humans were deduced through the model. The experimental analysis reveals that the randomness of the variation direction of a single virus does not affect the certainty of the development direction of the virus population variation. In other words, the pathogenicity intensity of the virus population continues to decrease until it stabilizes in the low-value range, and the infectious intensity of the virus population continues to increase until it stabilizes in the high-value range. The key external parameters that affect the virus transmission variation process are given, which can provide policy recommendations for the early prevention and control of highly pathogenic viruses.

Key words: virus transmission model, multi-agent simulation, prevention and control strategies, development trend of epidemic virus characteristics, genetic variation

中图分类号:

TP391.9

于雷,朱喜绸,廖华明等 . 病毒传播变异与人群交叉活动的相互影响及扩散模型研究[J]. 系统仿真学报, 2024, 36(7): 1713-1728.

Yu Lei,Zhu Xichou,Liao Huaming,et al . Interaction Between Virus Transmission Variation and Population Crossover Activity and Diffusion Model[J]. Journal of System Simulation, 2024, 36(7): 1713-1728.

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infect_inten	概率分布/%
加1或减1	70
加2或减2	20
加3或减3	5
加4或减4	3
加5或减5	1
加6或减6	0.7
加7或减7	0.3
其他	0

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