复杂网络上基于演化博弈理论的疾病动力学建模研究

项目名称： 复杂网络上基于演化博弈理论的疾病动力学建模研究

项目编号： No.61304156

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 自动化技术、计算机技术

项目作者： 曹崀

作者单位： 郑州大学

项目金额： 23万元

中文摘要： 近年来，人类社会不断受到日益严重的大规模爆发传染病的威胁，针对性的疾病防控策略成为复杂网络疾病传播动力学研究中的重要课题。一方面，相关的反疾病措施（例如疫苗接种等）,通常在非强制性的实施原则下,群集中的每个个体需要进行决策，其过程不仅取决于病情的危害、策略的代价，更受其他人决策行为的影响。而演化博弈论提供了复杂网络环境下个体策略交互学习的理论框架，通过建立和研究博弈模型，模拟真实个体对疾病传播的行为反应，从而更好的达到降低传染病危害的目的。另一方面，我们关注病毒层面的演化建模，例如最常见的，病毒变异所产生的新株系会直接导致原有疫苗在一段时间后失效的可能性。演化博弈论同样为病毒演化动力学中涉及到的多株系病原体间竞争、互惠、交叉免疫等相互作用提供了良好的刻画。借助演化博弈论来理解和揭示疾病传播、病毒演化等现象的内在机制，不仅对疾病防控策略研究具有重要的现实意义，同时也为我们开拓了新的研究视野。

中文关键词： 网络扩散；演化博弈；记忆效应；疫苗接种；搭档选择

英文摘要： In recent years, humans have been more and more frequently suffered from large-scale outbreaks of infectious epidemics that are increasingly threatening the entire human society, like severe acute respiratory syndrome (SARS) in 2003, avian influenza (bird flu) and pandemic influenza (H1N1) in 2009. On one hand, much attention of researchers has been focused on the related study on outbreak control measures for infectious epidemics. If not being involuntary, anti-epidemic strategies (such as the vaccination policy) typically allow individuals of a population to self-decide whether to take up vaccine or not, in which case individual decisions are heavily affected not only by their varied beliefs or experiences about the risk from infection and the implementation cost of vaccination, but also, more importantly, by others' decisions. Evolutionary game theory provides a universal framework to model such individual interactions. In particular, game-theoretical models (e.g., the vaccine game) have been proposed and investigated to mimic the reality of individual behavioral response to the spread of infectious diseases on complex networks, which successfully guides the collective behavior of a population of individuals to achieve a lowered risk of infection. On the other hand, our interest is also on to evolutionary-gam

英文关键词： Networked Diffusion；Evolutionary Game；Memory Effect；Vaccination；Partner Choice