Multiscale Modelling and Infection Probability of Sars-Cov-2 Transmission in a Typical Lecture Theatre

As worldwide educational institutions are returning to face-to-face learning in the post-pandemic world, the unavoidable crowded lectures raises concerns about the readiness to maintain a safe learning environment against potential future outbreaks of SARS-CoV-2. This study employs a Eulerian-Lagrangian approach together with a dose-response model to assess transmission risks in a typical lecture theatre. Our investigation focuses on continuous coughing scenarios to realistically represent conditions where infected individual frequently expels respiratory particles over an extended period and time. The novelty of this study lies in its comprehensive approach to practical transmission risk assessment, utilizing multiscale modelling for precise respiratory particle transport and infection risk evaluation. Results reveal that maintaining ventilation rates between 4 and 6 ACH significantly reduces virus concentrations while optimizing energy consumption. Infection probabilities are lower when the infectious source is near return air diffusers (median probability approximately 0.1) comparing to areas near the supply air diffusers (median probability around 0.4). However, reducing occupancy density does not uniformly decrease infection risks. Maintaining a 2-meter distance may not necessarily suffice in mitigating airborne transmission, as these measures primarily address large respiratory particles. Overall, this study provides data-driven recommendations to optimize ventilation and reduce transmission risks, supporting safer in-person learning environments.