公私协同视角下突发疫情应急医疗资源动态调度研究

突发疫情下，根据疫情演化趋势来决策政府、社会救援力量协同下的应急资源调度方案，是疫情防控指挥决策中的现实需求，而现有研究却比较薄弱。本项目基于“公私协同”视角并采用“数据驱动”方法研究该问题：首先，建立数据驱动的资源调度框架模型，利用传染病模型预测疫情趋势，根据疫情演化决策资源调度，运用信息熵、贝叶斯方法修正参数；其次，针对公私协同下城市外部资源供给调度、城市内部资源按需调度，结合最优停时、风险评价、网络优化理论及方法，依次构建供货商“能力差异”下的供货启动时间点选择与订单分配模型、“职责分工差异”下的政府与承运商协同物资配送模型，将其嵌入数据驱动决策框架，并设计动态求解算法；最后，结合武汉新冠疫情实例进行仿真分析并归纳策略建议。本项目将疫情下的需求预测、采购、分配和配送路径进行集成优化设计，研究成果可有效刻画疫情演化与资源调度的动态交互效应，获得实时有效的公私协同调度决策。

Once an epidemic occurs, it is a practical requirement for decision makers to dynamically coordinate emergency medical resources with the collaboration of public and private sectors and according to the evolution trend of the epidemic. However, very little research has been done. We study the problem of resource coordination under an epidemic from the perspective of “public-private collaboration” and with the method of “data driven”. .Firstly, we will develop a data-driven model for coordinating emergency medical resources according to the evolution trend of the epidemic. In this model, we will first predict the epidemic evolution trend by proposing a variant epidemic model, then make resource coordination decisions according to the evolution trend predicted, and finally modify the model parameters with the methods of information entropy and Bayesian. Secondly, we aim at searching both optimal external and internal resource coordination strategies from the perspective of public-private collaboration. On one hand, we will develop a supplier section and order distribution model with difference of suppliers’ capability by combining theories of stop time, risk evaluation, and network optimization. On the other hand, we will develop collaborative resource distribution models by considering different responsibilities between public and private sectors. These models will be embedded into the data-driven framework model, and the dynamic solution algorithms will also be proposed. Finally, we will carry out simulation analysis according to relevant data of the Wuhan COVID-19 epidemic. .This project integrates and optimizes the problems including demand forecasting, resource procurement and distribution under an epidemic. The results not only effectively depict the dynamic interaction effect between the epidemic evolution and the resource coordination, but also obtain real-time and effective resource coordination strategies from the mode of public-private collaboration.