Numerical Simulation of Spread and Infection Risk of Respiratory Pathogens in the Aircraft Cabin

Authors

Jiaquan Lin, Institute of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China;
Fengshan Sun, Institute of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China;
Yachong Li, Institute of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China;

Abstract

Abstract: In order to study the transmission law of respiratory pathogens through the breath of the sick passengers in the aircraft cabin and reduce the risk of infection, the numerical model of respiratory pathogens spread in Boeing737 economy cabin is established. The dynamic propagation process of respiratory pathogens released by the sick passenger is simulated. The risk of infection for other passengers is obtained. Taking SEI (Susceptible Exposure Index) as an evaluation index,,the seats with the least risk of infection for other passengers are obtained based on the simulated data by changing the seats of the sick passengers. Some seats of the sick passengers with the highest risk of infection for the remaining passengers are analyzed. The results provide a theoretical basis for studying respiratory pathogen transmission and the prediction of infection risk in the aircraft cabin.

Recommended Citation

Lin, Jiaquan; Sun, Fengshan; and Li, Yachong (2019) "Numerical Simulation of Spread and Infection Risk of Respiratory Pathogens in the Aircraft Cabin," Journal of System Simulation: Vol. 31: Iss. 8, Article 7.
DOI: 10.16182/j.issn1004731x.joss.18-0701
Available at: https://dc-china-simulation.researchcommons.org/journal/vol31/iss8/7

First Page

1541

Revised Date

2019-03-12

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.18-0701

Last Page

1547

CLC

V245.3

Recommended Citation

Lin Jiaquan, Sun Fengshan, Li Yachong. Numerical Simulation of Spread and Infection Risk of Respiratory Pathogens in the Aircraft Cabin[J]. Journal of System Simulation, 2019, 31(8): 1541-1547.

DOI

10.16182/j.issn1004731x.joss.18-0701