Several intense policies, such as mandatorily wearing masks and practicing social distancing, have been implemented in South Korea to prevent the spread of the novel coronavirus disease (COVID-19). In this study, we analyzed and measured the impact of the aforementioned policies by calculating the degree of infection exposure in public transportation. Specifically, we simulated how passengers encounter and infect each other during their journeys in public transportation by tracking movements of passengers. The probabilities of exposure to infections in public transportation were compared via a combination of the aforementioned policies by using the SEIR model, a respiratory infectious disease diffusion model. We determined that the mandatorily wearing of masks exhibits similar effects to maintaining social distancing 2 m in preventing COVID-19. During peak hours, in the cases of mandatorily wearing and practicing social distancing with masks, the reduction in infection rates corresponded to 93.5% and 98.1%, respectively.