Virus transmission analysis and visualization based on agent-based modeling

doi:10.11772/j.issn.1001-9081.2025020213

Journal of Computer Applications ›› 2026, Vol. 46 ›› Issue (2): 497-504.DOI: 10.11772/j.issn.1001-9081.2025020213

• Advanced computing • Previous Articles

Virus transmission analysis and visualization based on agent-based modeling

Haiyue CHEN¹, Xiuwen YI²^,³(), Shan YAN¹, Shijiao LI¹, Tianrui LI¹, Yu ZHENG¹^,²^,³

^1.School of Computing and Artificial Intelligence，Southwest Jiaotong University，Chengdu Sichuan 611756，China
^2.JD Intelligent Cities Research，Beijing 100176，China
^3.JD iCity （Beijing） Digital Technology Company Limited，Beijing 100176，China

Received:2025-03-06 Revised:2025-04-15 Accepted:2025-04-18 Online:2025-04-24 Published:2026-02-10
Contact: Xiuwen YI
About author:CHEN Haiyue， born in 2000， M. S. candidate. Her research interests include urban computing， visual analysis.
YI Xiuwen， born in 1991， Ph. D.， associate research fellow. His research interests include urban computing， deep learning， data mining. Email:xiuwenyi@foxmail.com
YAN Shan， born in 2001， M. S. candidate. His research interests include urban computing.
LI Shijiao， born in 2000， M. S. candidate. His research interests include urban computing， spatio-temporal data mining.
LI Tianrui， born in 1969， Ph. D.， professor. His research interests include big data intelligence， urban computing， granular computing and rough sets.
ZHENG Yu， born in 1979， Ph. D.， professor. His research interests include urban computing， spatio-temporal data mining， big data analytics of intelligent cities.
Supported by:
National Key Research and Development Program of China(2023YFC2308703)

基于主体建模的病毒传播分析与可视化

陈海乐¹, 易修文²^,³(), 严山¹, 黎世骄¹, 李天瑞¹, 郑宇¹^,²^,³

^1.西南交通大学计算机与人工智能学院，成都 611756
^2.北京京东智能城市大数据研究院，北京 100176
^3.京东城市（北京）数字科技有限公司，北京 100176

通讯作者: 易修文
作者简介:陈海乐（2000—），女，四川成都人，硕士研究生，CCF会员，主要研究方向：城市计算、可视分析
易修文（1991—），男，浙江衢州人，副研究员，博士，CCF高级会员，主要研究方向：城市计算、深度学习、数据挖掘 Email:xiuwenyi@foxmail.com
严山（2001—），男，湖北荆州人，硕士研究生，主要研究方向：城市计算
黎世骄（2000—），男，四川成都人，硕士研究生，主要研究方向：城市计算、时空数据挖掘
李天瑞（1969—），男，福建莆田人，教授，博士，主要研究方向：大数据智能、城市计算、粒计算与粗糙集
郑宇（1979—），男，湖南衡阳人，教授，博士，主要研究方向：城市计算、时空数据挖掘、智能城市大数据分析。
基金资助:
国家重点研发计划项目(2023YFC2308703)

Abstract

Abstract:

In recent years， respiratory infectious diseases break out in crowded places frequently. How to restore transmission path of the virus between people has become a key issue in epidemic prevention and control. However， the existing methods have problems such as the difficulty in describing the crowd movement trajectory in crowded places and the difficulty in simulating spread of the virus caused by contact between people. To this end， a virus transmission’s visual analysis system of Agent-Based Modeling （ABM） was proposed to simulate dynamically and visualize the virus transmission process as well as show individual contact relationships and transmission paths. Firstly， a multi-head rapidly-exploring random tree algorithm was combined with movement statistical data to generate crowd movement trajectories conforming to actual laws. Secondly， by refining the contact rules of people and the virus transmission mechanism， a transmission model based on ABM was constructed to simulate the impact of crowd interaction on virus transmission. Case analysis shows that the virus transmission’s visual analysis system restores the contact relationship between people and the process of virus transmission between people， the transmission chain simulated by the system is highly similar to the actual chain， the number of simulated cases is basically consistent with the actual number of cases， and the multi-head rapidly-exploring random tree algorithm can generate highly realistic trajectories efficiently. The case verifies the decision support value of the system in the optimization of epidemic prevention and control strategies.

Key words: visual analysis, transmission and diffusion, Agent-Based Modeling (ABM), trajectory simulation, virus transmission

摘要：

近年来呼吸道传染病在人员密集场所频繁暴发，如何还原病毒在人与人之间的传播路径，成为疫情防控的关键问题。然而，现有方法存在对密集场所中的人群移动轨迹难以刻画以及对人与人接触导致的病毒扩散难以模拟等问题。因此，提出一种基于主体建模（ABM）的病毒传播可视分析系统，以动态模拟并可视化病毒的传播过程，同时展现个体接触关系和传播路径。首先，采用多头快速扩展随机树算法结合移动统计数据，生成符合实际规律的人群移动轨迹；其次，通过细化人员接触规则和病毒扩散机制，构建基于ABM的传播模型，从而模拟人群交互对病毒传播的影响。案例分析表明，病毒传播可视分析系统还原了人与人之间的接触关系和病毒在人与人之间的传播过程，系统模拟的传播链路与实际链路高度相似，模拟病例数与实际病例数基本吻合，且多头快速扩展随机树算法能高效生成高度真实的路线。案例证实了该系统在疫情防控策略优化中的决策支持价值。

关键词: 可视分析, 传播扩散, 基于主体建模, 轨迹仿真, 病毒传播

CLC Number:

TP399

Haiyue CHEN, Xiuwen YI, Shan YAN, Shijiao LI, Tianrui LI, Yu ZHENG. Virus transmission analysis and visualization based on agent-based modeling[J]. Journal of Computer Applications, 2026, 46(2): 497-504.

陈海乐, 易修文, 严山, 黎世骄, 李天瑞, 郑宇. 基于主体建模的病毒传播分析与可视化[J]. 《计算机应用》唯一官方网站, 2026, 46(2): 497-504.

Figures/Tables 9

Fig. 1 Architecture of proposed system

Fig. 2 Path tree expansion process

Fig. 3 Interface of proposed system

Fig. 4 Case transmission process

Fig. 5 Changes in virus load in cases

Fig. 6 Generating trajectory coverage map

Fig. 7 Number of endpoints and algorithm efficiency

Fig. 8 Transmission link comparison

Fig. 9 Comparison of daily cumulative cases

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Virus transmission analysis and visualization based on agent-based modeling

基于主体建模的病毒传播分析与可视化

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