  Corona Virus Disease 2019 (COVID-19), due to its extremely high infectivity,
has been spreading rapidly around the world and bringing huge influence to
socioeconomic development as well as people's daily life. Taking for example
the virus transmission that may occur after college students return to school,
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 proposed in this
paper, fully considering 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 experimental results show that the proposed
model in this paper efficiently simulate how the virus spread in the dense
crowd in frequent contact under closed environment. Furthermore, preventive and
control measures such as self-protection, crowd decentralization and isolation
during the epidemic can effectively delay the arrival of infection peak and
reduce the prevalence, and finally lower the risk of COVID-19 transmission
after the students return to school.
