Enhancing Resilience in Construction Against Infectious Diseases Using Stochastic Multi-Agent Approach

Nima Gerami Seresht*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
60 Downloads (Pure)

Abstract

To recover from the adverse impacts of COVID-19 on construction and to avoid further losses to the industry in future pandemics, the resilience of construction industry needs to be enhanced against infectious diseases. Currently, there is a gap for modeling frameworks to simulate the spread of infectious diseases in construction projects at micro-level and to test interventions’ effectiveness for data-informed decision-making. Here, this gap is addressed by developing a simulation framework using stochastic agent-based modeling, which enables construction researchers and practitioners to simulate and limit the spread of infectious diseases in construction projects. This is specifically important, since the results of a building project case-study reveals that, in comparison to the general population, infectious diseases may spread faster among construction workers and fatalities can be significantly higher. The proposed framework motivates future research on micro-level modeling of infectious diseases and efforts for intervening the spread of diseases in construction projects.
Original languageEnglish
Article number104315
Pages (from-to)1-13
Number of pages13
JournalAutomation in Construction
Volume140
Early online date11 May 2022
DOIs
Publication statusPublished - 1 Aug 2022

Keywords

  • Infectious diseases
  • COVID 19
  • Resilience
  • Risk Management
  • Agent-Based Modelling
  • Monte Carlo Simulation

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