摘要
为探究个体行为变化在传染病传播过程中发挥的作用,以北京市为例构建基于个体的流感传播模型,并基于此对一种信息感知的个体行为模型进行计算机模拟。结果表明,个体行为变化能够有效降低疫情峰值水平和发病率;较短的信息感知区间能提高个体行为变化对疫情发展的抑制能力。研究结果对于加深对传染病传播行为的理解及有效的风险沟通有借鉴意义。
To explore the effects of human behavior change on the transmission of infectious diseases,the spreading of influenza was computed with a presented behavior model considering information perception based on a constructed individual-based epidemic model of Beijing.The results are as follows：human behavior change can lower the peak value of epidemics and attack rate,and this ability of inhibition would be enhanced considering a shorter interval of memory accumulation.These results have great reference significance for further understanding the spreading behavior of infectious diseases and effective risk communication.
出处
《生物技术通讯》
CAS
2016年第3期396-400,共5页
Letters in Biotechnology
基金
国家自然科学基金(71403287)
国家科技重大专项(2013ZX10004605)
全军医学科技(13QNP156)
关键词
行为变化
传染病传播模型
计算实验
behavior change
epidemic models
computational experiments
