Computational study and prediction of infection risk probability of respiratory diseases inside a classroom

The European Union has approved a new Ambient Air Quality Directive with stricter air quality standards. On this basis, providing suitable ventilation is a crucial factor in order to prevent the contagious respiratory diseases. To that end, computational fluid dynamics simulations are a valuable too...

Full description

Saved in:
Bibliographic Details
Main Authors: Oskar Urbina-Garcia, Iñigo Aramendia, Carolina Marugán-Cruz, Wilfried Coenen, Sergio Sánchez-Delgado, Unai Fernandez-Gamiz, Ekaitz Zulueta
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/19942060.2025.2514659
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The European Union has approved a new Ambient Air Quality Directive with stricter air quality standards. On this basis, providing suitable ventilation is a crucial factor in order to prevent the contagious respiratory diseases. To that end, computational fluid dynamics simulations are a valuable tool to evaluate indoor environments by different ventilation distributions. Initially, in the present study, four different Heating Ventilation Air Conditioning (HVAC) distributions were evaluated with one single human model placed in the middle of a typical classroom. The viral load exhaled by this individual was simulated with a tracer gas at different heights and the Infection Risk probability (IR) was quantified introducing the Wells-Riley mathematical model. The results foresee positioning inlet and outlet of HVAC systems as a factor of great impact in order to decrease this probability. Therefore, the ventilation layout providing the lowest passive scalar values was further studied simulating a classroom full of students. During the assessment, a good correlation in terms of temperature stratification with related literature was encountered. Also, the highest local Infection Risk (IR) of 16% was determined in a worst-case scenario for a specific individual located near the infectious source under poor ventilation efficiency. This value does not represent the classroom average, but a local maximum within the defined simulation parameters. In the meanwhile, members of the classroom closer to the ventilation output obtained the lowest IR of 6%. Nevertheless, high infection risk vales are typically observed for members located at the ventilation inlet area when infected individual is also there located. Thus, for the studied ventilation layout in a normal classroom configuration this work anticipates where the areas of greater and minor risk of infection could be located.
ISSN:1994-2060
1997-003X