A 3D-printed model of the human nose and upper airway that coughs and sneezes has provided researchers with valuable insight into how airborne infections are spread. This knowledge will be instrumental in developing effective strategies to minimize the transmission of such infections.
The global COVID-19 pandemic highlighted the ease with which respiratory diseases can spread through coughing and sneezing. Accurately replicating the transmission of airborne diseases is crucial for understanding their spread, but it is often challenging to recruit sick individuals for research purposes.
To address this issue, researchers from the Universitat Rovira i Virgili (URV) in Spain have created a 3D model of the human upper airway and nasal cavity that can simulate coughing and sneezing, allowing for a better study of how disease-carrying particles spread.
Catalán et al. 2024
The researchers were focused on creating a realistic respiratory model that accurately represents airflow dynamics, particle size, direction, and dispersion rate during coughing and sneezing. These factors play a significant role in disease transmission, hence the need for a lifelike model.
Using high-speed cameras and a laser beam, the researchers studied how particles disperse in the air in real-time. They examined particle cloud trajectory and width under various experimental conditions simulating different exhalation events through the nose or mouth.
The study revealed that exhaling through the nose deflects infectious particles downward, leading to more vertical dispersion but longer airborne suspension. On the other hand, exhaling through the mouth results in infectious particles traveling further in a horizontal path, increasing the risk of infection spread to individuals in close proximity.
Universitat Rovira i Virgili
Nicolás Catalán, the lead author of the study and a researcher at URV’s Department of Mechanical Engineering, emphasized the importance of understanding particle dispersion in indoor spaces and how diseases are transmitted through the air.
While further research is required to explore the impact of environmental factors like humidity and temperature on particle dispersion, the current findings can inform ventilation strategies in various settings such as restaurants, classrooms, hospitals, and public transport.
The researchers concluded that optimizing ventilation systems based on particle cloud dynamics could significantly reduce the risk of airborne disease transmission.
The study was published in the journal Physics of Fluids.
Source: Universitat Rovari i Virgili
