Prediction of the areal trends of COVID-19 epidemic based on markov-chain
In the COVID-19 epidemic environment,in order to accurately predict the number of people with different symptom states and the development trend at the regional level,based on the SIR infectious disease model and the spatio-temporal correlation under Markov chain prediction,designs the K-SIRD infectious disease prediction model related to the infected population state and the control measures.According to the characteristics of the contagious-ness among the COVID-19 epidemic population and the transfer law of different symptomatic state changes caused by the changes in the effective number of infectious Re affected by dis-tance,the real-time accurate prediction of the changes in the number of people in different states,and according to the distribution of the symptomatic state of the population in the same area is different,different levels of control measures are used for different levels of the area.
K-SIRD modelCOVID-19Markov-chainthe effective reproduction number
万方数据
维普
