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Investigation of Coronavirus Deposition in Realistic Human Nasal Cavity and Impact of Social Distancing to Contain COVID-19: A Computational Fluid Dynamic Approach.
- Source :
- CMES-Computer Modeling in Engineering & Sciences; 2020, Vol. 125 Issue 3, p1185-1199, 15p
- Publication Year :
- 2020
-
Abstract
- The novel coronavirus responsible for COVID-19 has spread to several countries within a considerably short period. The virus gets deposited in the human nasal cavity and moves to the lungs that might be fatal. As per safety guidelines by theWorld Health Organization (WHO), social distancing has emerged as one of the major factors to avoid the spread of infection. However, different guidelines are being followed across the countries with regards to what should be the safe distance. Thus, the current work is an attempt to understand the virus deposition pattern in the realistic human nasal cavity and also to find the impact of distance that could be termed as a safety measure. This study is performed usingComputationalFluid Dynamics as a solution tool to investigate the impact of COVID-19 deposition (i) On a realistic 3D human upper airway model and (ii) 2D social distancing protocol for a distance of 0.6, 1.2, 1.8, and 2.4 m. The results revealed that the regional deposition flux within the nasal cavity was predominantly observed in the external nasal cavity and nasopharyngeal section. Frequent flushing of these regions with saltwater substitutes can limit contamination in healthy individuals. The safe distancing limit estimated with 1 m/s airflow was about 1.8 m. The extensive deposition was observed for distances less than 1.8 m in this study, emphasizing the fact that social distancing advisories are not useful and do not take into account the external dynamics associated with airflow. [ABSTRACT FROM AUTHOR]
- Subjects :
- SOCIAL distancing
NASAL cavity
COVID-19
SARS-CoV-2
AIR flow
Subjects
Details
- Language :
- English
- ISSN :
- 15261492
- Volume :
- 125
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- CMES-Computer Modeling in Engineering & Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 147695228
- Full Text :
- https://doi.org/10.32604/cmes.2020.015015