大数据环境中自愿接种策略及个体安全保护方法研究

Voluntary vaccination strategy and individual security protection inabig data environment

大数据背景下,如何充分利用数据分析、挖掘等方法有效发现传染病传播规律,对于疾病防控、个体的安全保护有着重要作用和意义.自愿接种是对群体获得广泛免疫和安全保护的有效方式.以往的研究中,个体根据以往传播过程中的患病风险或者收益来确定是否进行自愿接种,如个体与其邻近的邻居比较上一个季节获得的收益来决定是否采用邻居的策略,也就是说策略更新对于群体的安全保护至关重要.本文研究了不同的策略更新方式对自愿接种行为的影响.通过比较个体采用不同的策略更新方式所获得的群体平均接种比例、疾病暴发规模和社会总花费,研究并设计出合理的策略更新方式,即在花费成本比较低的情况下,获得比较大的群体平均接种比例和较小的疾病覆盖率.

In era of big data,how to make full use of data analysis and data mining to effectively detect the spreadof infectious diseases is of great significance for epidemic prevention control as well as for individual security.Vol-untary vaccination is an effective way to achieve broad immunity and safety protection for the whole population.Pre-vious research results have showed that an individuals decision on voluntary vaccination is mainly based upontradeoff between the infection risk and the protective profit,in which the decision of the individuals neighbors in lastseason is of impact,indicating the influence of strategy-updating for the collective security and protection.This paperstudies into the effect of different strategy updates on the voluntary vaccination.The average proportion of vaccina-tion,epidemic scale and total social cost are compared between different strategy updates.Thereafter,a reasonablestrategy-updatingisdesigned to achieve relatively big vaccination coverage and small disease outbreak scale with rela-tively low social cost.