Dynamic vaccine distribution model based on epidemic diffusion rule and clustering approach

基于传染病扩散规律和聚类分析的动态疫苗配送模型(英文)

Due to the fact that the emergency medicine distribution is vital to the quick response to urgent demand when an epidemic occurs, the optimal vaccine distribution approach is explored according to the epidemic diffusion rule and different urgency degrees of affected areas with the background of the epidemic outbreak in a given region. First, the SIQR （susceptible, infected, quarantined,recovered） epidemic model with pulse vaccination is introduced to describe the epidemic diffusion rule and obtain the demanded vaccine in each pulse. Based on the SIQR model, the affected areas are clustered by using the self-organizing map （SOM） neutral network to qualify the results. Then, a dynamic vaccine distribution model is formulated, incorporating the results of clustering the affected areas with the goals of both reducing the transportation cost and decreasing the unsatisfied demand for the emergency logistics network. Numerical study with twenty affected areas and four distribution centers is carried out. The corresponding numerical results indicate that the proposed approach can make an outstanding contribution to controlling the affected areas with a relatively high degree of urgency, and the comparison results prove that the performance of the clustering method is superior to that of the non-clustering method on controlling epidemic diffusion.

针对当传染病发生时医药物资的配送对于应急需求响应至关重要这一特点,以在一定区域内发生传染病疫情为研究背景,根据传染病扩散规律和疫区紧急救助程度的不同,研究了具有多个疫区和多个应急配送中心的疫苗配送最优方案.引入具有脉冲接种的SIQR模型来描述传染病的扩散规律和获得各区域疫苗需求量,在SIQR模型的基础上,利用SOM神经网络将各疫区进行聚类并量化结果.以实现运输成本和缺货量最小为目标,在聚类的基础上建立了动态的疫苗配送模型.以20个受感染区域和4个分布中心为例,给出了算例和仿真分析,结果表明所提出的方法有助于控制具有较高紧急等级区域的疫情,且与不使用聚类方法进行疫苗配送相比,利用聚类方法能更好地控制疫情扩散.