摘要
较为全面的综述复杂网络的免疫问题,包括:真实疫情和舆情传播场景的抽象与建模、疾病传播模型、全局免疫策略和局域免疫策略等。在若干真实网络和模型网络上模拟免疫控制的结果表明,基于中心性、图划分、熟人免疫等策略的免疫效果比随机免疫好,这说明免疫策略的选择对传播控制具有实际指导意义。在选择免疫策略时,应考虑网络的拓扑结构特性和信息的完整程度,才能达到较佳控制效果。
In this paper,an overview of vaccination methods addressing in suppressing the epidemic spreading is given,focusing on modeling the epidemic and public sentiment spreading from real world scenarios,describing models of dynamic spreading,and presenting vaccination strategies and their efficiency.Simulation results on empirical networks and model networks using different vaccination strategies show that vaccination strategies such as centrality-based vaccination,graph partition-based vaccination and acquaintance vaccination are more effective than random vaccination.This implies that vaccination strategy is important and meaningful in suppressing epidemic spreading.In order to reach a better control result,the topological structure and the completeness of network information should be taken into account when choosing a vaccination strategy.
出处
《复杂系统与复杂性科学》
EI
CSCD
北大核心
2016年第1期74-83,共10页
Complex Systems and Complexity Science
基金
国家自然科学基金(11105025
91324002)
西南石油大学科研启航计划(2014QHZ024)
关键词
复杂网络
传播动力学
疫情与舆情
网络免疫
complex network
spreading dynamics
epidemic and public sentiment spreading
network vaccination
