A computational model for the evolution of infectious diseases driven by social networks and individual behavior: cross layer interaction mechanism and digital governance strategy

LI Fang; ZHOU Deyu; WANG Gang; XUE Xiao; LIU Guangjun; HU Qi

doi:10.11959/j.issn.2096-6652.202544

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A computational model for the evolution of infectious diseases driven by social networks and individual behavior: cross layer interaction mechanism and digital governance strategy

Topics\：Social Computing and Resilient Society | 更新时间：2026-03-18

- A computational model for the evolution of infectious diseases driven by social networks and individual behavior: cross layer interaction mechanism and digital governance strategy
- Chinese Journal of Intelligent Science and Technology Vol. 7, Issue 4, Pages: 533-542(2025)
- 作者机构：
  
  1.西安财经大学信息学院，陕西西安 710100
  2.智财协同可信计算陕西省高等学校重点实验室，陕西西安 710100
  3.山东大学软件学院，山东济南 250101
  4.天津大学智能与计算学部，天津 300072
  5.西安文理学院信息工程学院，陕西西安 710065
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(62472306);The Foundation of China (Xi’an) Institute for Silk Road Research(2019HZ03)
- DOI：10.11959/j.issn.2096-6652.202544
  CLC： TP39
- Received：30 September 2025，
  
  Revised：2025-12-28，
  
  Accepted：30 December 2025，
  
  Published：15 December 2025
- 稿件说明：
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李芳,周德雨,王刚等.社会网络与个体行为驱动的传染病演化计算模型：跨层交互机制与数字治理策略[J].智能科学与技术学报,2025,07(04):533-542.

LI Fang,ZHOU Deyu,WANG Gang,et al.A computational model for the evolution of infectious diseases driven by social networks and individual behavior: cross layer interaction mechanism and digital governance strategy[J].Chinese Journal of Intelligent Science and Technology,2025,07(04):533-542.
李芳,周德雨,王刚等.社会网络与个体行为驱动的传染病演化计算模型：跨层交互机制与数字治理策略[J].智能科学与技术学报,2025,07(04):533-542. DOI： 10.11959/j.issn.2096-6652.202544.

LI Fang,ZHOU Deyu,WANG Gang,et al.A computational model for the evolution of infectious diseases driven by social networks and individual behavior: cross layer interaction mechanism and digital governance strategy[J].Chinese Journal of Intelligent Science and Technology,2025,07(04):533-542. DOI： 10.11959/j.issn.2096-6652.202544.

摘要

个体行为的随机性、社会关系的复杂性、防控策略的滞后性等因素，使传染病的传播过程呈现出高动态性与强不确定性。这对传染病的演化分析提出新的挑战。现有研究通过多层网络建模和个体行为分析，在疾病传播、行为演化和政策干预等方面取得了重要进展，但在跨层闭环机制的系统化建模方面仍不足，难以充分解释个体行为、社会网络结构、防控策略之间的耦合关系。基于此，从整体上刻画“政策、行为、传播和反馈”的动态交互过程，提出一种基于社会网络与个体行为的传染病演化计算模型，包含个体层、组织层和社会层3个互联层次。最后，通过分析计算实验在不同策略下的各类型Agent存活数量和最终达到的稳定状态这两个指标，验证此模型的有效性。

Abstract

The randomness of individual behavior

the complexity of social relationships

and the lag in prevention and control strategies make the transmission process of infectious diseases highly dynamic and uncertain. This poses new challenges to the analysis of the evolution of infectious diseases. Existing research has made significant progress in disease transmission

behavioral evolution

and policy intervention through multi-layer network modeling and individual behavior analysis. However

there is still insufficient systematic modeling of cross-layer closed-loop mechanisms

which makes it difficult to fully explain the coupling relationship between individual behavior

social network structure

and prevention and control strategies. This paper describes the dynamic interaction process of “policy

behavior

dissemination

and feedback” as a whole

and proposes a computational model for the evolution of infectious diseases based on social networks and individual behavior

which includes three interconnected levels: individual level

organizational level

and social level. Finally

the effectiveness of this model was verified by analyzing and calculating the number of surviving agents of various types under different strategies and the final stable state achieved in the experiment.

关键词

Keywords

references

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