Research On Demand Prediction And Allocation Optimization Of Emergency Medical Resources For Public Health Emergencies

The outbreak of novel coronavirus pneumonia in late 2019 has gradually evolved into a worldwide public health emergency.As of February 8,2022,novel coronavirus pneumonia patients worldwide were diagnosed more than 398 million 420 thousand,and the cumulative death rate was over 5 million 760 thousand.Novel coronavirus pneumonia virus mortality is a serious threat to people’s lives.High infectious and high variability make great challenges to the epidemic prevention and control.For the sudden occurrence of such public health events,under the premise of limited information and difficult to prevent and control in advance,the use of systematic emergency disposal to reduce the losses caused by the events will become the primary task of prevention and control.In the emergency decision support system as the core of emergency disposal technology,emergency medical resources are generally regarded as the main decision-making object.However,in the actual situation,due to the uncertainty of the time and place of the event,it is impossible to accurately predict the time of demand and the disaster point;Moreover,due to the uncertainty of the number of people affected by the incident,the number of resources for production scheduling is difficult to be consistent with the actual needs,and the allocation of emergency medical resources for public health emergencies cannot be carried out accurately.In addition to the difficulty of resource prediction,the problem of resource allocation has always been prominent.In the case of limited resources,how to allocate resources to maximize the utilization of resources and maximize the number of people treated;And how to allocate resources to ensure the fairness of resource allocation and ensure that different types of patients can receive fair treatment,these two points often become the focus of emergency resource allocation decision-making.Reasonable resource prediction needs to adjust the proportion of resource allocation in combination with the model on the basis of obtaining the information of the number of people affected on that day,so as to make the prediction of the number of resources more accurate,so as to ensure the order and reliability of the implementation of the emergency rescue plan.Reasonable resource allocation needs to consider the utilization rate of limited resources and the fairness of allocation on the basis of accurate prediction,so as to ensure the efficiency and sustainability of emergency rescue.Therefore,this paper takes covid-19 as the research background.Firstly,based on the existing SEIR infectious disease dynamics model,combined with Dirichlet distribution and Bayesian dynamic update,this paper forecasts the number of patients of different types,and predicts the demand quantity of different types of materials according to the number of patients;Secondly,based on the predicted quantity of materials,considering the full and partial satisfaction of resources,study the efficiency of resource allocation,further consider the pain degree of different types of patients,and study its impact on the number of treated patients and the proportion of resource allocation;Then,on the premise of maximizing the total number of treatment,add the fairness goal of resource allocation,explore the loss of fairness to allocation efficiency,provide reasonable emergency medical resource allocation scheme and provide valuable reference for decision-makers according to the research results of each part.