Abstract: At present, the prevention and control of major outbreaks has caused a huge impact on the public system, and the characteristics of sudden, emergency, diffusion and high uncertainty are becoming more and more prominent, and the emergency management problems of major outbreaks need to be solved urgently. For example, during the COVID-19 epidemic, the shortage of protective materials, the imbalance of material distribution, and the asymmetry of supply and demand of emergency supplies have caused supply and deployment of epidemic prevention materials to be seriously insufficient. Therefore, in order to accurately respond to the surge of material demand in major disasters, the balanced distribution and cross-regional deployment of materials are extremely important. Based on this research background, the SIR model is established in this study, and the model parameter combination is obtained through software simulation. On this basis, the dynamic data set of the material demand subject is established, and then the supply and demand quantity of emergency supplies is determined according to the quantity of research samples. At present, a large number of scholars at home and abroad have predicted and analyzed the demand for emergency supplies in emergencies such as the COVID-19 epidemic. For example, some scholars use ARIMA and adaptive filtering methods to predict the demand of medical services. In addition, another study has established an adaptive evolutionary support vector regression model to predict post-earthquake emergency blood demand. On this basis, scholars propose an improved GM(1,1) model to predict the demand of emergency supplies after flood disaster, or use CBR technology to predict the demand of emergency supplies after the earthquake. The case reasoning technology needs to find the appropriate source case to achieve more accurate prediction; The gray prediction model can be predicted by a small amount of incomplete information. But the major outbreak is different from all previous kinds of infectious diseases, in which the information contains high uncertainty and complexity, so the existing research analysis model is lack of applicability. Considering the COVID-19 as an infectious disease, the infectious disease system dynamics, and its obvious difference from previous similar diseases, the improved dynamic analysis model is used. According to previous studies, many scholars have used the infectious disease model to study the development trend of the epidemic situation, and few scholars have linked it to the demand for emergency supplies.
In view of this, in order to more accurately describe the demand for emergency supplies during the Wuhan epidemic, the material needs are described according to the national classification standards, and the traditional model is improved according to the true spread of the epidemic. Wuhan COVID-19 epidemic history data are collected through COVID by parameter calibration and parameter comparison experiments. In this study, the traditional infectious disease model is modified and set innovatively on this basis: (1)According to the notice of the diagnosis and treatment plan issued by the National Health Commission, the incubation period is infectious, and the isolation observation period, incubation period and average disease period are set. (2)The population during the incubation period is redefined. The incubation period includes two types of isolation and unisolated observation, which are divided into carrying and not carrying the virus. The virus population will become the key groups of the spread of the epidemic due to the lack of isolation measures. (3)The cured patients will not be transmitted by the existing patients (the possibility of positive recovery is very low). (4)Inpatients are treated in a strictly controlled isolation ward, depending on the part of the population that is unable to infect susceptible patients. The results show that: (1)The change in the number of contacts, infection rate, detection rate, virus proportion and other indicators will directly affect the number of people infected by major epidemics. (2)Changes in the number of contacts, infection rate, discovery rate and other indicators will have an indirect impact on material demand. (3)During the epidemic period, China has adopted the strictest control measures such as urban and family quarantine to effectively reduce the spread range of the epidemic, and improve the detection rate with big data and other technologies. The parameter comparison experiments effectively verify that these measures are beneficial to relieving the huge supply pressure of emergency supplies. By establishing a dynamic model system of infectious diseases in the epidemic period, the inevitable connection between material demand and epidemic prevention and control is effectively verified, and the purpose of dispatching cross-regional emergency supplies and accurately matching supply and demand is achieved through analysis, providing an important reference for dealing with major disasters such as similar epidemics. On the basis of balancing the supply and demand of emergency supplies during the epidemic period, constructing a dynamic model of infectious diseases and the demand analysis model of emergency supplies can further broaden the path of dealing with the demand of similar emergencies, so as to provide important theoretical reference for similar emergencies. In addition, there are still some research limitations in this study, that is, the deployment of materials among specific regions after the end of the outbreak needs further research.

Key words: COVID-19 outbreak, emergency supplies, SEIRD dynamic model, retrospective analysis

摘要： 为解决重大疫情下国内各地应急物资存储量分布失衡、区域性物资需求严重紧缺情况下的物资跨区域调配问题,对疫情期间所需的应急物资品种进行分类后提出了一种运用SEIRD传染病系统动力学理论的应急物资动态需求模型。以武汉市新冠肺炎疫情为例,对疫情传播整体态势和应急物资的需求量进行仿真和回溯性分析。通过模型的参数对比实验发现感染率、接触人数、发现率等指标和应急物资的需求量存在高度相关关系,研究结果验证了采取严格的疫情防控措施能够有效缓解区域性应急物资短缺局势,以期为未来类似突发事件下应急物资跨区域紧急救援计划的制定提供有力参考。

关键词: 新冠肺炎疫情, 应急物资, SEIRD动力学模型, 回溯性研究