行为决策过程对免疫–疾病双层网络耦合的影响研究

Study on the Influence of Behavioral Decision-Making Processes on the Coupling of Immune-Disease Dual-Layer Networks

摘要: 突发公共卫生事件中，疾病的传播不仅受到生物病理机制的影响，还与人群的免疫行为扩散紧密相关。在复杂的社会系统中，疾病传播过程实质上是一个与个体免疫决策相互交织、共同演化的动态过程。为了深入剖析免疫行为的决策过程和疾病传播的共演化传播特性，以及疾病传播的内在传播机理，研究者构建了免疫–疾病双层耦合网络模型，在免疫层引入演化博弈理论(EGT)，借鉴理性经济人假设，来量化个体在免疫行为决策过程中的成本效益分析。并利用微观马尔可夫链方法(MMCA)描绘了这一动态系统的演变规律，通过推导并确立了流行病阈值。通过蒙特卡洛(MC)模拟仿真验证了疫苗效力、接种成本及疫苗失效风险对疾病传播规模的实际影响，最终，研究强化了优化免疫策略在有效防控疫情方面所扮演的关键角色，并据此提出了相应的管理学建议。

Abstract: During public health emergencies, disease transmission is not only influenced by biological factors but also closely related to the diffusion of immune behaviors in the population. In complex social systems, disease spread is essentially a dynamic process that involves individual immune decision-making and coevolution. To better understand the decision-making process of immune behaviors, the coevolutionary transmission characteristics of disease spread, and the underlying transmission mechanism, researchers have developed a dual-layer immune-disease coupled network model. This model incorporates Evolutionary Game Theory (EGT) in the immune layer and uses the assumption of rational economic agents to quantify the cost-benefit analysis of individuals in their immune behavior decision-making. Using the Micro Markov Chain Approach (MMCA), researchers have described the evolution of this dynamic system and established an epidemic threshold. Monte Carlo (MC) simulations have been used to verify the actual impact of vaccine efficacy, vaccination costs, and vaccine failure rates on the scale of disease transmission. Finally，The study highlights the critical role of optimizing immune strategies in effectively controlling epidemics and offers corresponding management recommendations.