Abstract:Objective To construct the demand model of four types of medical resources including beds in hospital, beds in intensive care unit (ICU), ventilators and medical human resources during the major infectious disease epidemic events, simulate and analyze the treatment of infectious diseases when different medical resources are in short supply. Methods Based on the susceptible-exposed-infectious-recovered (SEIR) model, considering the infectivity of infected persons, the susceptibility of the population and the immunity of convalescents, the characteristics of asymptomatic COVID-19 patients and different clinical types, the "COVID-19 infection-hospitalization model" was constructed. By collecting and setting the parameters of disease transmission, clinical course and medical resource shortage scenarios, an analysis model of allocation and supply of urban medical resources during infectious di-sease epidemic events was initially formed based on Anylogic platform, the supply and demand of medical resources during infectious disease events in different scenarios were analyzed. Results In the non-intervention scenario, the peak time of bed demand was on the 107th day, and the peak value was 160.92 beds per thousand people; the peak time of ventilator demand was on the 122nd day, and the peak value was 5.61 units per thousand people; the peak time of ICU bed demand was on the 117th day, and the peak value was 12.78 beds per thousand people; the peak time of the demand for medical human resources was on the 109th day, and the peak value was 151.12 persons per thousand persons. The simulation Results suggested that there were some differences in the impact of different medical resources on the outcome of medical treatment. Conclusion This study constructs an analytical tool for the allocation and supply of urban medical resources under the epidemic events of infectious diseases, and the Results of multiple simulation experiments suggest that bed resources and medical human resources play more important roles in the outcome of medical treatment.