Predicting the trends and cost impact of COVID-19 OSHA citations on US construction contractors using machine learning - Research paper

Aug 5, 2026

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This study examines how COVID-19 case levels and construction employment relate to OSHA citations and quantifies the total and monthly predicted cost impact of OSHA citations tied to COVID-19 violations. Multiple regression and a supervised machine learning linear regression model using K-fold cross validation were applied, complemented by a probabilistic risk-based cost estimate via Monte Carlo simulation. Data were compiled from OSHA, CDC, and WHO sources. Results link higher monthly employment with fewer citations, while citation cost impact rises with COVID-19 cases.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages19

Reading Time48 min

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Abstract

Purpose and research aim

Design and methodology

Findings and relationships

Originality and implications

The current issue and full text archive of this journal is available on Emerald Insight at: [https://www.emerald.com/insight/0969-9988.htm](https://www.emerald.com/insight/0969-9988.htm) Predicting the trends and cost COVID-19 OSHA citations impact of COVID-19 OSHA citations on US construction contractors using machine learning 3461 and simulation Received 30 October 2021 Revised 6 March 2022 Hooman Sadeh and Claudio Mirarchi Accepted 6 April 2022 Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Milan, Italy Farzad Shahbodaghlou Department of Engineering, California State University East Bay, Hayward, California, USA, and Alberto Pavan Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Milan, Italy Abstract Purpose – Occupational Safety and Health Administration (OSHA) of the U.S. government ensures that all health and safety regulations, protecting the workers, are enforced. OSHA officers conduct inspections and assess fines for non-compliance and regulatory violations. Literature discussion on the economic impact of OSHA inspections with COVID-19 related citations for the construction sector is lacking. This study aims to investigate the relationships between the number of COVID-19 cases, construction employment and OSHA citationsandit further evaluates the total and monthly predicted cost impact of OSHA citations associated with COVID-19 violations. Design/methodology/approach – An application of multiple regression analysis, a supervised machine learning linear regression model, based on K-fold cross validation sampling and a probabilistic risk-based cost estimate Monte Carlo simulation were utilized to evaluate the data. The data were collected from numerous websites including OSHA, Centers for Disease Control and the World Health Organization. Findings–The results show that as the monthly construction employment increased, there was a decrease in OSHA citations. Conversely, the cost impact of OSHA citations had a positive relationship with the number of COVID-19 cases. In addition, the monthly cost impact of OSHA COVID-19 related citations along with the total cost impact of citations were predicted and analyzed. Originality/value – The application of the two models on cost analysis provides a thorough comparison of predicted and overall cost impact, which can assist the contractors to better understand the possible cost ramifications. Based on the findings, it is suggested that the contractors include contingency fees within their contracts, hire safety managers to implement specific safety protocols related toCOVID-19and request a safety action plan when qualifying their subcontractors to avoid potential fines and citations. Keywords COVID-19, Construction industry, Monte Carlo simulation, Machine learning, Cost analysis, OSHA, Safety, Risk management, Risk-based cost estimate Paper type Research paper © Hooman Sadeh, Claudio Mirarchi, Farzad Shahbodaghlou and Alberto Pavan. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4 .0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at [http://creativecommons.org/licences/by/4.0/](http://creativecommons.org/licences/by/4.0/)[ ](http://creativecommons.org/licences/by/4.0/)legalcode Engineering, Construction and Architectural Management Vol. 30 No. 8, 2023 pp. 3461-3479 Emerald Publishing Limited 0969-9988 DOI 10. 1108/ECAM-10-2021-0953 ECAM Introduction 30,8 COVIDand hea-19lthheas hadlementas msianjorce t,adheversstarte woforthldewspidereaimd, pact onand speeconcificoalmlyica,fsoteciralth,eenvironmentaWorld Healthl Organization (WHO) announced it as

FAQs

What relationships does the study investigate between COVID-19 and OSHA citations?

The study evaluates relationships between the number of COVID-19 cases, construction employment, and OSHA citations, including the cost impact tied to COVID-19-related violations.

What methods are used to estimate citations and their costs?

It applies multiple regression and a supervised machine learning linear regression model with K-fold cross validation, and uses a Monte Carlo simulation to generate probabilistic risk-based cost estimates.

What are the key findings regarding employment, citations, and COVID-19 cases?

As monthly construction employment increases, OSHA citations decrease. The cost impact of OSHA citations shows a positive relationship with the number of COVID-19 cases.

Aug 5, 2026

Upload by Jiven