  Corona Virus Disease 2019 (COVID-19), due to its extremely high infectivity,
has been spreading rapidly around the world and brought huge influence to
socioeconomic development as well as people's production and life. Taking for
example the virus transmission that may occur after college students return to
school during the outbreak, we analyze the quantitative influence of the key
factors on the virus spread, including crowd density and self-protection. One
Campus Virus Infection and Control Simulation model (CVICS) of the novel
coronavirus is designed in this paper, based on the characteristics of repeated
contact and strong mobility of crowd in the closed environment. Specifically,
we build an agent-based infection model, introduce the mean field theory to
calculate the probability of virus transmission, and micro-simulate the daily
prevalence of infection among individuals. The simulation experiment results
show that the proposed model in this paper fully illuminate how the virus
spread in the dense crowd. Furthermore, preventive and control measures such as
self-protection, crowd decentralization and quarantine during the epidemic can
effectively delay the arrival of infection peak and reduce the prevalence, and
thus lower the risk of COVID-19 transmission after the students return to
school.
