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According to the World Health Organization (WHO), the COVID-19 pandemic has caused a huge loss of human life and posed unprecedented challenges to public health. The outbreak of COVID-19 forced governments worldwide to impose various restrictions, including mobility restrictions, socio-economic restrictions, and social distancing regulations, to reduce the spread of the disease (de Bruin et al., 2020). Although these restrictions have positively impacted the spread of COVID-19, they have caused significant losses to the construction industry (Jones et al., 2020). As social distancing was the main way to curtail the spread of the pandemic, the construction sector was severely affected because of the labourintensiveness of the execution of construction projects. Despite the implementation of strict restrictions, previous studies have revealed that the construction industry has the highest COVID-19 infection rate among other industries such as medical care, manufacturing and transportation, with a hospitalisation rate that was five times the average level of other industries (Allan-Blitz et al., 2020; Pasco et al., 2020). Recent studies, particularly in epidemiology, have shown how different statistical and modelling techniques such as linear programming, dynamic programming, structural equation modelling, and agent-based modelling (ABM) can predict the spread of COVID-19 (Saldaña and Velasco-Hernández, 2022; Afzal et al., 2022). However, there is limited research reviewing which modelling techniques could be used to understand how construction workers interact, resulting in predicting the transmission rate on site. In addition, the …