# Transportation and Reserve of Emergency Medical Supplies during Public Health Events
## 3 Materials and Methods  
### Forecast of Emergency Medical Supply Demand and Model for Mobilization and Stockpiling  
#### 3.1.1 Prediction Model of Infected People Based on SEIRD  
The SEIR (susceptible, exposed, infectious, recovered) model, as the most basic system dynamics model of infectious diseases [24], studies the dynamic mechanism of infectious diseases in the transmission process and provides a theoretical basis for the prevention and treatment of infectious diseases. The SEIR epidemic model can effectively simulate public health issues. Basic public health event models of infectious diseases include SI,SIR, SIRS, SEIR, etc. In order to solve the models, ordinary differential equations, partial differential equations, and network dynamics are studied. Based on the SEIR model and considering the new characteristics of modern public health issues, this paper assumes that the new identity \(D\) stands for Dead. There are also many unfortunate deaths in modern public health issues, and the inclusion of the new identity \(D\) in the model allows the model to simulate a situation that is more closely related to a modern public health issue, without increasing the computational complexity of the model. The SIERD model is more plausible than the SEIR model. In addition, there are many other methods for prediction of public health event situations, such as deep ensemble learning methods for COVID-19 prediction [25]. This method requires training of the model and produces a model with high accuracy in predicting results but is not model specific and requires a large data base. There are also studies that estimate COVID-19 trends using the ARIMA model, which consists of an autoregressive (AR), integral (I), and moving average (MA) model [26; 27]. However, the model requires a static time series and lacks accuracy in the early stages of time and lacks advantages in its wide application to the prediction of public health issues. Normally the SEIRD model is simpler to fit, and the formula is more intuitive. However, the SEIRD model has certain requirements on the setting of parameters, which need to be supported by scientific data to fit, such as the parameter \"latency period\", which should also be set in conjunction with the actual clinical research. This paper is a comprehensive study of public health issues. The SEIRD model has a wider applicability, and the data format of the prediction is five categories of people, which brings convenience to the subsequent prediction of the demand for emergency medical supplies in this paper. Therefore, the SEIRD model is more applicable to the context of this paper. Although modern public health issues have the characteristics of a long latent period, the SEIRD model can simulate modern public health issues more appropriately, among which the following are:  
\(S\) stands for Susceptible, which refers to a person who is not yet sick but is susceptible to the virus and will become an \"\(E\)\" sometime after being infected by an \"\(I\)\";  
\(E\) stands for Exposed, which refers to the person who has been in contact with an infected person but is temporarily unable to infect others. Such people carry a virus and have a certain incubation period and will become a susceptible person;  
\(I\) stands for Infectious, which refers to a person infected with the virus who is already sick and who can transmit the virus to susceptible people and convert them into members of class \(E\);  
\(R\) stands for Recovered, which refers to a person who has been quarantined from the system, or who has recovered, and who will not be infected;  
\(D\) stands for Dead, which refers to a person who has died during the event and cannot be turned into another type of identity.