Ruifeng Cao
The transmission of COVID-19 in construction: A systematic review of findings from statistical and modelling techniques
Cao, Ruifeng; Cheung, Clara; Yunusa-Kaltungo, Akilu; Manu, Patrick; Liu, Chunxue; Qiao, Qingyao
Authors
Clara Cheung
Akilu Yunusa-Kaltungo
Patrick Manu Patrick.Manu@uwe.ac.uk
Professor of Innovative Construction and Project Management
Chunxue Liu
Qingyao Qiao
Contributors
Patrick Manu Patrick.Manu@uwe.ac.uk
Editor
Clara Cheung
Editor
Akilu Yunusa-Kaltungo
Editor
Fidelis Emuze
Editor
Tarcisio Abreu Saurin
Editor
Bonaventura Hadikusumo
Editor
Abstract
The COVID-19 outbreak experienced in late 2019 continues to impact work patterns significantly. The construction sector has been severely affected because of the labour-intensiveness of typical construction sites. Recent studies, particularly in epidemiology, have shown how different modelling techniques can predict the spread of COVID-19. However, the approach for selecting the most appropriate modelling method for workers’ health and safety in the construction industry against COVID-19 is still unclear. This study aims to develop an awareness of how the construction industry could use the simulation and modelling techniques to manage the transmission risks at construction sites. A systematic literature review based on the PRISMA guidelines has been conducted focusing on modelling applications in the spread of COVID-19 in construction, with specific interest in the modelling purposes and limitations to guide researchers to select appropriate modelling techniques. Research identified five commonly used simulation and modelling techniques in construction industry for COVID-19 transmission: 1) SIR/SEIR modelling, 2) Agent-based modelling, 3) Statistical modelling, 4) Building information modelling, and 5) Artificial Intelligence approach. Nineteen relevant articles were included in the detailed review based on criteria, and a comprehensive comparison of these five modelling techniques was produced. The review reveals that each of these techniques have their unique characteristics/strengths that make them useful for modelling COVID-19 transmission risk in construction under various scenarios or stages of the pandemic.
Online Publication Date | Sep 12, 2023 |
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Publication Date | Jan 1, 2024 |
Deposit Date | Mar 19, 2024 |
Publisher | Taylor & Francis (Routledge) |
Pages | 15-27 |
Book Title | Construction Safety, Health and Well-being in the COVID-19 era |
Chapter Number | 2 |
ISBN | 9781032229157 |
DOI | https://doi.org/10.1201/9781003278368-3 |
Public URL | https://uwe-repository.worktribe.com/output/11832318 |
Publisher URL | https://www.taylorfrancis.com/chapters/edit/10.1201/9781003278368-3/transmission-covid-19-construction-ruifeng-cao-clara-cheung-akilu-yunusa-kaltungo-patrick-manu-chunxue-liu-qingyao-qiao?context=ubx&refId=d721f61b-05ba-4569-a5e7-0db18db7b3f4 |
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