arXiv · 2212.07787
Modelling of human exhaled sprays and aerosols to enable real-time estimation of spatially-resolved infection risk in indoor environments
Abstract
A numerical framework for the 'real-time' estimation of the infection risk from airborne diseases (e.g., SARS-CoV-2) in indoor spaces such as hospitals, restaurants, cinemas or teaching rooms is proposed. The developed model is based on the use of computational fluid dynamics as a pre-processor to obtain the time-averaged ventilation pattern inside a room, and a post-processing tool for the computation of the dispersion of sprays and aerosols emitted by its occupants in 'real time'. The model can predict the dispersion and concentration of droplets carrying viable viral copies in the air, the contamination of surfaces, and the related spatially-resolved infection risk. It may therefore provide useful information for the management of indoor environments in terms of, e.g., maximum occupancy, air changes per hour and cleaning of surfaces. This work describes the fundamentals of the model and its main characteristics. The model was developed using open-source software and is conceived to be simple, user-friendly and highly automated to enable any potential user to perform estimations of the local infection risk.
Explore related subjects
Keep this discovery
Daniel Fredrich, Aliyah M. Akbar, Muhammad Faieq bin Mohd Fadzil, Afxentis Giorgallis, Alexander Kruse, Noah Liniger, Lazaros Papachristodoulou, Andrea Giusti. 2022-12-14. Modelling of human exhaled sprays and aerosols to enable real-time estimation of spatially-resolved infection risk in indoor environments. https://arxiv.org/abs/2212.07787
Cite the original work for its findings. Save a collection to share your selection of sources.