复杂社会经济条件下基于网络模型的传染病防控政策研究

Research on epidemic prevention and control policies based on a network model under complex socio-economic conditions

在复杂社会经济条件下研究传染病的动态传播机制和防控措施是一个重要的课题.本文将社会网络模型和流行病传播模型相结合,提出了基于社会接触网络的流行病传播模型(contacting network based S-E-I_(N)-I_(F),CNSEII).现有的静态社会网络难以体现防控政策对网络结构的影响,为弥补这一不足,本文搭建了以“个体-家庭-社会”为主体的无标度的三级网络.基于该网络结构的CNSEII模型能够刻画防控政策对疫情传播的动态影响,帮助制定科学有效的传染病防控政策.本文进一步提出并证明了疫情清零的必要性条件和防控隔离有效性定理,为科学防控重大突发传染病提供了理论支撑.本文应用仿真模拟对比了不同参数组合对疫情防控结果的影响.通过实验发现,病毒强弱和对病毒的筛查力度会显著影响疫情清零时间,在减少疫情感染人数方面,降低不同家庭之间的连接程度比直接影响个体节点与社会主网络的接触概率更加有效.

The prevalence and prevention of epidemic are influenced by complex socio-economic conditions.By integrating social network models and epidemic propagation models,we propose a contacting network based S-E-I_(N)-I_(F)(CNSEII)model to investigate dynamic transmission of epidemic.Unlike existing static social networks,which fail to capture the impact of control policies on network structures,this study addresses this limitation by constructing a three-level network comprising individuals,households,and the society,employing a scale-free structure as the foundation.The proposed CNSEII model,built upon this network structure,effectively captures the dynamic impact of control policies on epidemic transmission,helping to develop scientific and effective measures for epidemic prevention and control.Furthermore,we propose and prove the necessary condition for epidemic elimination and the effectiveness theorem of prevention and control measures,providing theoretical support for the scientific prevention and control of major infectious diseases.Through simulation,this study evaluates the impact of different parameter combinations on epidemic control outcomes.The experiments reveal that the virulence of the virus and the intensity of virus screening significantly influence the time required for epidemic elimination.Moreover,in terms of reducing the number of infected individuals,limiting interconnections between different households proves more effective than controlling the contact probability of individual nodes with the primary social network.