TY  - JOUR
PY  - 2022//
TI  - Prediction of time in industrial chemical accidents: a survival analysis
JO  - Work
A1  - Sadeghi, Fatemeh
A1  - Dehdashti, Alireza
A1  - Gilanic, Neda
A1  - Fatemi, Farin
A1  - Alizadeh, Seyed Shamseddin
A1  - Khoshmanesh, Behnoush
SP  - ePub
EP  - ePub
VL  - ePub
IS  - ePub
N2  - BACKGROUND: Chemical accidents have imposed casualties and high economic and social consequences to Iranian industries and society. <br><br>OBJECTIVE: This study investigated the effect of risk factors involved in occurrences of the chemical accidents and predicted the time of occurrences in Iranian chemical factories. <br><br>METHODS: A cross-sectional study was implemented in 574 chemical facilities with more than 25 employees from 2018 to 2020. Collecting data instruments were 2 checklists with 15 and 25 three-point Likert scale questions, respectively. Chi square and Monte Carlo tests assessed the relationships between independent risk factors and dependent hazardous chemical accidents. Cox semi-parametric and log-normal parametric models were used to predict the upcoming time of chemical accidents based on the impacts of risk factors understudy. Data analyses were performed using Stata and R software. <br><br>RESULTS: The results showed that safety data sheets, labeling, fire extinguishing system, safe chemicals storage, separation, loading, transportation and training were statistically significant with occurrences of the chemical accidents (P-value < 0.05). Loading and transportation were mostly related to chemical incidents and reduced significantly the expected time of chemical events (P-value = 0.028). <br><br>CONCLUSION: Establishing a comprehensive chemical accidents dataset and strict governmental supervision on chemical safety regulations are suggested to decrease the chemical accidents at regional and local levels in chemical plants.<p />  <p>Language: en</p>
LA  - en
SN  - 1051-9815
UR  - http://dx.doi.org/10.3233/WOR-211333
ID  - ref1
ER  -