SAfE transport: wearing face masks significantly reduces the spread of COVID-19 on trains
Grzybowska, Hanna, Hickson, R.I., Bhandari, Bishal, Cai, Chen, Towke, Michael, Itzstein, Benjamin, Jurdak, Raja, Liebig, Jessica, Najeebullah, Kamran, Plani, Adrian, El Shoghri, Ahmad, and Paini, Dean (2022) SAfE transport: wearing face masks significantly reduces the spread of COVID-19 on trains. BMC Infectious Diseases, 22 (1). 694.
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Abstract
COVID-19 has had a substantial impact globally. It spreads readily, particularly in enclosed and crowded spaces, such as public transport carriages, yet there are limited studies on how this risk can be reduced. We developed a tool for exploring the potential impacts of mitigation strategies on public transport networks, called the Systems Analytics for Epidemiology in Transport (SAfE Transport). SAfE Transport combines an agent-based transit assignment model, a community-wide transmission model, and a transit disease spread model to support strategic and operational decision-making. For this simulated COVID-19 case study, the transit disease spread model incorporates both direct (person-to-person) and fomite (person-to-surface-to-person) transmission modes. We determine the probable impact of wearing face masks on trains over a seven day simulation horizon, showing substantial and statistically significant reductions in new cases when passenger mask wearing proportions are greater than 80%. The higher the level of mask coverage, the greater the reduction in the number of new infections. Also, the higher levels of mask coverage result in an earlier reduction in disease spread risk. These results can be used by decision makers to guide policy on face mask use for public transport networks.
| Item ID: | 76355 |
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| Item Type: | Article (Research - C1) |
| ISSN: | 1471-2334 |
| Keywords: | COVID 19, Disease spread model, Face masks, SARS-CoV-2, Transit assignment |
| Copyright Information: | © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
| Date Deposited: | 24 Oct 2022 01:53 |
| FoR Codes: | 49 MATHEMATICAL SCIENCES > 4901 Applied mathematics > 490102 Biological mathematics @ 30% 35 COMMERCE, MANAGEMENT, TOURISM AND SERVICES > 3509 Transportation, logistics and supply chains > 350906 Public transport @ 30% 42 HEALTH SCIENCES > 4202 Epidemiology > 420205 Epidemiological modelling @ 40% |
| SEO Codes: | 20 HEALTH > 2004 Public health (excl. specific population health) > 200404 Disease distribution and transmission (incl. surveillance and response) @ 100% |
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