A novel approach to preventing SARS-CoV-2 transmission in classrooms: A numerical study

Abstract

The education sector has suffered a catastrophic setback due to the ongoing COVID pandemic, with classrooms being closed indefinitely. The current study aims to solve the existing dilemma by examining COVID transmission inside a classroom and providing long-term sustainable solutions. In this work, a standard 5 × 3 × 5 m3 classroom is considered where 24 students are seated, accompanied by a teacher. A computational fluid dynamics simulation based on OpenFOAM is performed using a Eulerian–Lagrangian framework. Based on the stochastic dose–response framework, we have evaluated the infection risk in the classroom for two distinct cases: (i) certain students are infected and (ii) the teacher is infected. If the teacher is infected, the probability of infection could reach 100% for certain students. When certain students are infected, the maximum infection risk for a susceptible person reaches 30%. The commonly used cloth mask proves to be ineffective in providing protection against infection transmission, reducing the maximum infection probability by approximately 26% only. Another commonly used solution in the form of shields installed on desks has also failed to provide adequate protection against infection, reducing the infection risk only by 50%. Furthermore, the shields serve as a source of fomite mode of infection. Screens suspended from the ceiling, which entrap droplets, have been proposed as a novel solution that reduces the infection risk by 90% and 95% compared to the no screen scenario besides being completely devoid of fomite infection mode. The manifestation of infection risk in the domain was investigated, and it was found out that in the case of screens the maximum infection risk reached the value of only 0.2 (20% infection probability) in 1325 s.