Size–Frequency Distribution Characteristic of Fatalities Due to Workplace Accidents and Industry Dependency

The exploration of the statistical characteristics and distribution patterns of workplace accidents can help to reveal the intrinsic features and general laws of safety issues, which is essential for forecasting and decision making in safe production. Here, we conduct the detailed analysis of the distribution characteristics between the fatality number and the frequency of workplace accidents based on the in-depth data mining of various industries. The results show that the distribution between the fatality number and the frequency of workplace accidents follows a power-law distribution. Moreover, the exponents of such power-law distributions in different industries exhibit significant industry dependence, with the characteristic values of the power-law exponents in the coal mining industry, the hazardous chemicals industry, the transportation industry, and the construction industry being 1.55, 2.16, 2.15, and 2.92, respectively. Meanwhile, the temporal variation in the power-law distribution exponent in each industry can be used for the short-term prediction and evaluation of safe production, which will inform the decision making of the safety management department. Last, but not the least, the results of this study provide the theoretical basis for Heinrich’s Law and confirm that a substantial reduction in the number of small-scale accidents can effectively help control the frequency of large-scale fatal accidents.

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Publication Details

Journal
Mathematics
Published
2025-06-19
DOI
https://doi.org/10.3390/math13122021
Primary Topic
Occupational Health and Safety Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Size–Frequency Distribution Characteristic of Fatalities Due to Workplace Accidents and Industry Dependency

Fang Zhou, Fuxiang Wang, Xiling Liu
Mathematics
Occupational Health and Safety Research
article

Size–Frequency Distribution Characteristic of Fatalities Due to Workplace Accidents and Industry Dependency

Fang Zhou, Fuxiang Wang, Xiling Liu
article en

Abstract

The exploration of the statistical characteristics and distribution patterns of workplace accidents can help to reveal the intrinsic features and general laws of safety issues, which is essential for forecasting and decision making in safe production. Here, we conduct the detailed analysis of the distribution characteristics between the fatality number and the frequency of workplace accidents based on the in-depth data mining of various industries. The results show that the distribution between the fatality number and the frequency of workplace accidents follows a power-law distribution. Moreover, the exponents of such power-law distributions in different industries exhibit significant industry dependence, with the characteristic values of the power-law exponents in the coal mining industry, the hazardous chemicals industry, the transportation industry, and the construction industry being 1.55, 2.16, 2.15, and 2.92, respectively. Meanwhile, the temporal variation in the power-law distribution exponent in each industry can be used for the short-term prediction and evaluation of safe production, which will inform the decision making of the safety management department. Last, but not the least, the results of this study provide the theoretical basis for Heinrich’s Law and confirm that a substantial reduction in the number of small-scale accidents can effectively help control the frequency of large-scale fatal accidents.

MathematicsVol. 13(12)
Central South University (CN)
National Natural Science Foundation of China, Central South University, Natural Science Foundation of Hunan Province, Fundamental Research Funds for the Central Universities, Fundamental Research Funds for Central Universities of the Central South University
Openalex Percentile: Top 80%
Occupational Health and Safety Research
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