A coupled Computational Fluid Dynamics and Wells-Riley model to predict COVID-19 infection probability for passengers on long-distance trains

Author:

Wang ZhaozhiORCID,Galea Edwin R.ORCID,Grandison Angus,Ewer John,Jia FuchenORCID

Funder

University of Greenwich

Publisher

Elsevier BV

Subject

Public Health, Environmental and Occupational Health,Safety Research,Safety, Risk, Reliability and Quality

Reference69 articles.

1. A rapid review of the engineering approaches to mitigate the risk of COVID-19 transmission on public transport, National Engineering Policy Centre, https://www.raeng.org.uk/publications/reports/a-rapid-review-of-the-engineering-approaches-to-mi (Accessed on 24th June 2021).

2. Anozie, P., 2020. RDG Guidance: Maintenance of On-Train HVAC Modules & Filters during the COVID-19 Pandemic, V1.1, Rail Delivery Group, UK, 26th May, 2020.

3. Estimating the nationwide transmission risk of measles in US schools and impacts of vaccination and supplemental infection control strategies;Azimi;BMC Infect. Dis.,2020

4. Bernal, B.J., Andrews, N., Gower, C., et al., 2021. Effectiveness of COVID-19 vaccines against the B.1.617.2 variant. medRxiv Preprint. Doi: 10.1101/2021.05.22.21257658.

5. Estimation of airborne viral emission: quanta emission rate of SARS-CoV-2 for infection risk assessment;Buonanno;Environ. Int.,2020

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