Infection and Prevention of COVID-19 in Schools Based on Real-Life Interpersonal Contact Data

Abstract

With the stabilization of the COVID-19 in China, the resumption of study has become the hottest issue most concerned by the people. The long-time gathering and face-to-face contact of students and teachers in schools increase the risk of their mutual infection. Although school suspension is generally considered to be the most feasible strategy to alleviate epidemics, large-scale isolation is often accompanied by high socio-economic costs and even social panic. Therefore, when an outbreak occurs in schools, we need to try to use more detailed scientific prevention and control measures. In this study, the spread of the COVID-19 in schools is simulated based on real interpersonal contact data, and the prevention and control measures are formulated by calculating the effective distance among students. This study finds that students have more contact with students in the same class and grade in schools. Therefore, when cases are found in schools, the development of the epidemic can be controlled by closing the patient's class and grade in time, and it will achieve similar or even better results than the closed school. In addition, in the absence of closure and the application of prevention and control measures, the impact of the proportion of asymptomatic patients and the incubation period infectivity in school outbreaks are analyzed, respectively. After the prevention and control measures are applied, the epidemic situation in each case will be controlled, and it will soon usher in a time when the epidemic situation improves. The research in this paper helps schools to select appropriate prevention and control measures, and accurately assess the impact of asymptomatic patients and incubation period infectivity on the epidemic.