# Transportation and Reserve of Emergency Medical Supplies during Public Health Events
## 8 Conclusions  
This paper focuses on the prediction of the number of people affected by public health issues, the prediction of the demand for emergency medical supplies, and the transportation and storage of emergency medical supplies. Compared to the general logistics system, the core of this paper is to consider the dynamic number of infected people under public health issues and the urgency of emergency medical material demand, and to present the dual goals of weak economy and timeliness of the emergency logistics system, that is, the shortest response time and the lowest delay cost. On this basis, a multistage optimal scheduling model is constructed to realize the decision-making management of emergency medical materials transportation and storage under public health emergencies. By constructing a model and solving it, we can realize the prevention and emergency transportation of public health issues and provide suggestions and theoretical support for the new modern public health issues in the future. The research results obtained in this paper are mainly reflected in the in-depth exploration and analysis of related fields:  
* Continue comprehensive analysis and research of the literature related to emergency logistics: This paper discusses the connotation of emergency logistics and emergency medical materials and focuses on the solution and application of related algorithms. It summarizes various methods and application scenarios of emergency materials demand prediction and vehicle dispatching optimal path solution based on the SEIR model of infection system dynamics and metaheuristic algorithm;
* Building demand forecasting model: Forecast the scale of demand for emergency medical supplies at the demand points. First, this paper uses the SEIRD model of system dynamics, uses the least-squares method to fit the parameters of the initial data on the pneumonia epidemic situation in COVID-19, Hubei province, and uses MATLAB to predict the epidemic situation in a certain period in the future. Second, based on the daily consumption of healthy people as a benchmark, this paper defines individual emergency medical materials, and then obtains the daily demand for emergency medical materials from various people, and the total demand for emergency medical materials of demand points by solving;
* Establishing a demand urgency function: In this paper, considering the dual factors that influence the epidemic prevention and control ability of the demand points and the urgency of the demand for emergency medical materials, the analysis of the principal component of the evaluation index system of the epidemic prevention and control ability is carried out by SPSS, and the urgency function of the demand of the epidemic prevention and control ability is established. Then, the urgency function of the demand for emergency medical materials is established using the predicted demand for emergency medical materials demand. Finally, the total urgency function of demand is designed according to the two designed demand urgency functions;
* Establishing the path optimization model: In this paper, a vehicle routing optimization model is established, which takes into account the constraints of dual objectives, demand urgency, and time window constraints. With the objective of minimizing the penalty cost for delay and the response time of the system, the vehicle routing optimization model is established combined with the constraints required by the model, and the approximate optimal solution of the model is carried out by using a Python design particle swarm optimization algorithm;
* Simulation example: This paper combines theory with practice, constructs a distribution network with six nodes in Jiangsu, and simulates it with demand forecasting model and vehicle routing model.