Evidence map›Paper›PMID 36712895›Full record

ArticleSafety science2023

The impact of COVID-19 pandemic on construction safety in China and the U.S.: A comparative study.

Pinsheng Duan, Yang Miang Goh, Jianliang Zhou

Abstract read
In one paragraph

Article in Safety science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Pinsheng DuanSchool of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China.
Yang Miang GohDepartment of the Built Environment, College of Design and Engineering, National University of Singapore, 4 Architecture Dr, Singapore 117566, Singapore.
Jianliang ZhouSchool of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many studies indicated that the COVID-19 pandemic had significant impacts on construction safety. However, the studies had differing views on whether the pandemic increased or decreased construction safety performance. Furthermore, past studies did not adopt a comparative time series approach to evaluate the impact of the pandemic on construction safety. Thus, this study explores the differences in the impact of the COVID-19 pandemic on construction safety in China and the United States. This study used SciNet to forecast the number of construction accidents without the pandemic. Subsequently, the forecast was compared with the actual number of accidents since the outbreak, and the analysis showed a reduced number of construction accidents during the pandemic. However, there were minimal changes and even a slight worsening of fatality rates. Moreover, the correlation analyses showed that the effect of the pandemic on construction safety was weak and lagging. Construction safety was significantly affected by the pandemic in China, and the impact is relatively rapid. In comparison, outbreaks did not have a major impact on construction safety in the U.S. in the early stage. Since the pandemic is still raging worldwide, this research helps governments or project stakeholders formulate more targeted and data-driven safety countermeasures to improve construction safety during the crisis. The study also helps nations respond to future pandemics and crises to prevent adverse effects on construction safety.

Indexed as

Comparative analysisConstructionCOVID-19 pandemicSafety accidentTime series

Identifiers

PMID36712895
PMCPMC9868398

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.