Optimal Patients and Material Distribu-tion to Combat COVID in Wuhan based on Nonlinear Programming

Haochen Wang

Xi'an Gaoxin No.1 High School, AP2，710075, China

Abstract: COVID-19 broke out in Wuhan, China, in January 2020. The COVID-19 virus is highly contagious and has a long incubation period, which led to the closure of Wuhan city by the Chinese government on January 23 after the outbreak was announced on January 22. In the following 10 days, Wuhan experienced an explosive increase in confirmed cases. Although the state deployed a large number of personnel and material resources to support Wuhan's fight against the epidemic, the outbreak was so fierce that Wuhan's medical system experienced huge challenges in terms of epidemic prevention and control, material supply and treatment capacity. During this period, there were constant news reports that due to the rapid emergence of COVID-19 infection symptoms in all parts of Wuhan, the response of the patient placement and material distribution system was slow and the management was chaotic. In order to cope with the situation in Wuhan during the epidemic, this paper selected five hospitals in Wuhan that were the first batch of patients designated by the government to receive COVID-19 patients, and explored the allocation scheme over 10 days of patients and medical supplies with the goal of minimizing the cost by using nonlinear optimization. The paper studied respectively different ways of considering total cost when the unsatisfactory cost of denying admission to each COVID-19/ general inpatient was considered/disregarded and the practical problem was transformed into a standard nonlinear programming problem, demonstrating the optimal cost and optimal allocation of patients and medical resources in both cases. When cross-infection in hospital is taken into account, it is believed that the greater the number of patients relative to the capacity of the hospital, the greater the frequency of contact between non-infected people in the hospital and infected people, and the higher the risk of cross-infection. The cross-infection rate of COVID-19 in hospital is in direct proportion to the density of patients.

Keywords: Nonlinear programming, COVID-19, Wuhan, Distribution, Recieve and cure patients