2021/10/22 by Donggyun Ku, Chihyung Yeon, Seungjae Lee +4 · 54 citations
Mathematics · Medicine · Environmental Science · Engineering · #COVID-19 epidemiological studies #Infection Control and Ventilation #COVID-19 impact on air quality #Coronavirus disease 2019 (COVID-19) #Social distance #2019-20 coronavirus outbreak #Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) #Public transport #Business #Virology #Internet privacy #Computer science #Medicine #Transport engineering #Engineering #Outbreak
paper · doi:10.1126/sciadv.abg3691
published in Science Advances 7(43), eabg3691 (American Association for the Advancement of Science)
openalex publication_date 2021/10/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
Several intensive 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). We analyzed and measured the impact of the aforementioned policies by calculating the degree of infection exposure in public transport. Specifically, we simulated how passengers encounter and infect each other during their journeys in public transport by tracking movements of passengers. The probabilities of exposure to infections in public transport via the aforementioned preventive measures were compared by using the Susceptible, Exposed, Infected, and Recovered model, a respiratory infectious disease diffusion model. We determined that the mandatory wearing of masks exhibits effects similar to maintaining 2-m social distancing in preventing COVID-19. Mandatory wearing of masks and practicing social distancing with masks during peak hours reduced infection rates by 93.5 and 98.1%, respectively.