Skip navigation

Inflight transmission of COVID-19 based on experimental aerosol dispersion data

Inflight transmission of COVID-19 based on experimental aerosol dispersion data

Wang, Zhaozhi ORCID: 0000-0002-8986-0554, Galea, Edwin R. ORCID: 0000-0002-0001-6665, Grandison, Angus ORCID: 0000-0002-9714-1605, Ewer, John ORCID: 0000-0003-0609-272X and Jia, Fuchen ORCID: 0000-0003-1850-7961 (2021) Inflight transmission of COVID-19 based on experimental aerosol dispersion data. Journal of Travel Medicine, 28 (4):taab023. ISSN 1195-1982 (Print), 1708-8305 (Online) (doi:https://doi.org/10.1093/jtm/taab023)

[img] PDF (Author's Accepted Manuscript)
30915 GALEA_Inflight_Transmission_of_COVID-19_(AAM)_2021.pdf - Accepted Version
Restricted to Repository staff only until 13 March 2022.

Download (516kB) | Request a copy
[img]
Preview
PDF (Author Submitted Manuscript)
30915 GALEA_Inflight_Transmission_of_COVID-19_(PrePrint)_2021.pdf - Submitted Version
Available under License Creative Commons Attribution.

Download (516kB) | Preview
[img]
Preview
PDF (Supplementary Material)
30915 GALEA_Supplemental_Material_(PrePrint)_2021.pdf - Supplemental Material
Available under License Creative Commons Attribution.

Download (257kB) | Preview

Abstract

Background:
An issue of concern to the travelling public is the possibility of in-flight transmission of COVID-19 during long- and short-haul flights. The aviation industry maintains that the probability of contracting the illness is small based on reported cases, modelling and data from aerosol dispersion experiments conducted on-board aircraft.

Methods:
Using experimentally derived aerosol dispersion data for a B777–200 aircraft and a modified version of the Wells-Riley equation we estimate inflight infection probability for a range of scenarios involving quanta generation rate and face mask efficiency. Quanta generation rates were selected based on COVID-19 events reported in the literature while mask efficiency was determined from the aerosol dispersion experiments.

Results:
The MID-AFT cabin exhibits the highest infection probability. The calculated maximum individual infection probability (without masks) for a 2-hour flight in this section varies from 4.5% for the ‘Mild Scenario’ to 60.2% for the ‘Severe Scenario’ although the corresponding average infection probability varies from 0.1% to 2.5%. For a 12-hour flight, the corresponding maximum individual infection probability varies from 24.1% to 99.6% and the average infection probability varies from 0.8% to 10.8%. If all passengers wear face masks throughout the 12-hour flight, the average infection probability can be reduced by approximately 73%/32% for high/low efficiency masks. If face masks are worn by all passengers except during a one-hour meal service, the average infection probability is increased by 59%/8% compared to the situation where the mask is not removed.

Conclusions:
This analysis has demonstrated that while there is a significant reduction in aerosol concentration due to the nature of the cabin ventilation and filtration system, this does not necessarily mean that there is a low probability or risk of in-flight infection. However, mask wearing, particularly high-efficiency ones, significantly reduces this risk.

Item Type: Article
Additional Information: The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license. *** This article is a preprint and has not been peer-reviewed. It reports new medical research that has yet to be evaluated and so should not be used to guide clinical practice.
Uncontrolled Keywords: COVID-19 SARS-CoV-2; public and global health
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Liberal Arts & Sciences
Faculty of Liberal Arts & Sciences > Centre for Numerical Modelling & Process Analysis (CNMPA)
Faculty of Liberal Arts & Sciences > Centre for Numerical Modelling & Process Analysis (CNMPA) > Fire Safety Engineering Group (FSEG)
Faculty of Liberal Arts & Sciences > School of Computing & Mathematical Sciences (CAM)
Related URLs:
Last Modified: 31 Aug 2021 15:46
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/30915

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics