TY - JOUR
T1 - Modeling the factors that influence exposure to SARS-CoV-2 on a subway train carriage
AU - Miller, Daniel
AU - King, Marco-Felipe
AU - Nally, James
AU - Drodge, Joseph R.
AU - Reeves, Gary, I
AU - Bate, Andrew M.
AU - Cooper, Henry
AU - Dalrymple, Ursula
AU - Hall, Ian
AU - Lopez-Garcia, Martin
AU - Parker, Simon T.
AU - Noakes, Catherine J.
N1 - Funding Information:
MFK, AMB, IH, MLG, and CJN were supported by the : project ‐ EPSRC, EP/V032658/1‐. DM, JN, JRD, GIR, HC, UD, and STP were supported by the UK Department for Transport. The authors would like to thank the rest of the TRACK team, the EPSRC VIRAL project, Transport for London, and UK transport stakeholders on our steering boards for valuable insights as we have carried out this study. Content includes material subject to © Crown copyright (2021), Dstl. This material is licensed under the terms of the Open Government Licence except where otherwise stated. To view this license, visit http://www.nationalarchives.gov.uk/doc/open‐government‐licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: [email protected] . The underlying data used to create the graphs is available at 10.6084/m9.figshare.16912795. TRACK Transport Risk Assessment for COVID Knowledge
Publisher Copyright:
© 2022 Crown copyright. Indoor Air published by John Wiley & Sons Ltd. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland.
PY - 2022/2/15
Y1 - 2022/2/15
N2 - We propose the Transmission of Virus in Carriages (TVC) model, a computational model which simulates the potential exposure to SARS-CoV-2 for passengers traveling in a subway rail system train. This model considers exposure through three different routes: fomites via contact with contaminated surfaces; close-range exposure, which accounts for aerosol and droplet transmission within 2 m of the infectious source; and airborne exposure via small aerosols which does not rely on being within 2 m distance from the infectious source. Simulations are based on typical subway parameters and the aim of the study is to consider the relative effect of environmental and behavioral factors including prevalence of the virus in the population, number of people traveling, ventilation rate, and mask wearing as well as the effect of model assumptions such as emission rates. Results simulate generally low exposures in most of the scenarios considered, especially under low virus prevalence. Social distancing through reduced loading and high mask-wearing adherence is predicted to have a noticeable effect on reducing exposure through all routes. The highest predicted doses happen through close-range exposure, while the fomite route cannot be neglected; exposure through both routes relies on infrequent events involving relatively few individuals. Simulated exposure through the airborne route is more homogeneous across passengers, but is generally lower due to the typically short duration of the trips, mask wearing, and the high ventilation rate within the carriage. The infection risk resulting from exposure is challenging to estimate as it will be influenced by factors such as virus variant and vaccination rates.
AB - We propose the Transmission of Virus in Carriages (TVC) model, a computational model which simulates the potential exposure to SARS-CoV-2 for passengers traveling in a subway rail system train. This model considers exposure through three different routes: fomites via contact with contaminated surfaces; close-range exposure, which accounts for aerosol and droplet transmission within 2 m of the infectious source; and airborne exposure via small aerosols which does not rely on being within 2 m distance from the infectious source. Simulations are based on typical subway parameters and the aim of the study is to consider the relative effect of environmental and behavioral factors including prevalence of the virus in the population, number of people traveling, ventilation rate, and mask wearing as well as the effect of model assumptions such as emission rates. Results simulate generally low exposures in most of the scenarios considered, especially under low virus prevalence. Social distancing through reduced loading and high mask-wearing adherence is predicted to have a noticeable effect on reducing exposure through all routes. The highest predicted doses happen through close-range exposure, while the fomite route cannot be neglected; exposure through both routes relies on infrequent events involving relatively few individuals. Simulated exposure through the airborne route is more homogeneous across passengers, but is generally lower due to the typically short duration of the trips, mask wearing, and the high ventilation rate within the carriage. The infection risk resulting from exposure is challenging to estimate as it will be influenced by factors such as virus variant and vaccination rates.
KW - SARS-CoV-2 modeling
KW - airborne
KW - close-range
KW - fomite
KW - subway
KW - subway train carriage
U2 - 10.1111/ina.12976
DO - 10.1111/ina.12976
M3 - Article
SN - 0905-6947
VL - 32
JO - Indoor Air
JF - Indoor Air
IS - 2
M1 - e12976
ER -