An Empirical Study on Patient Queuing after Medical Staff Supporting Disaster Areas in Northwest China

Recently, the new coronavirus has brought great disaster to human beings, so we have to take strong measures to suppress the large-scale outbreak of the disease. In this paper, by looking up the data of medical staff supporting Wuhan area in Northwest China, we build a queuing model of M|M|C|∞ to analyze the waiting time and staying time of patients. Secondly, due to the increase of patients, the burden of outpatient service is gradually increasing, which leads to the speed of epidemic spread greatly accelerated. Therefore, SIR model is constructed to analyze the relationship between patients and healers. The experimental results show that: (1) at the beginning of the data of more than 1000 medical staff, the patients were served for too long, which led to low efficiency. When they were supported, the efficiency was increasing with the increase of support, and the time was shortened, which was very helpful to relieve the medical pressure of outpatient. (2) With the increase of patients, at the same time, the number of healers is increasing, of course, there are also healthy people in it. At this time, we should focus on finding a suitable node, reducing the number of patients and increasing the number of healers, so as to effectively control the epidemic.