通过使用基于SIR模型的普通微分方程来确定职业事故动态的新方法
Selcan Kaplanvural1,2, Eren Tosyalı3, İsmail Ekmekçi4
1Vocational School of Health Services, Occupational Health and Safety, İstanbul Bilgi University, Istanbul, 34387, Turkey. selcan.cicek@bilgi.edu.tr.
Scientific reports
|October 14, 2024
概括
本研究引入了一种职业事故动态模型 (OA模型) 来预测事故数量. 研究结果表明,加强职业健康和安全 (OHS) 培训有效地减少了职业事故.
科学领域:
- 流行病学 流行病学
- 数学建模的数学建模
- 职业安全 在职业安全.
背景情况:
- 职业事故在全球范围内构成重大风险.
- 动态模型对于理解和预测事故趋势至关重要.
- 现有的模型可能无法完全捕捉职业事故动态的细微差别.
研究的目的:
- 开发和验证一个新的职业事故动态模型 (OA模型).
- 使用数学技术分析OA模型的稳定性和行为.
- 评估职业健康和安全 (OHS) 重新培训对减少事故的影响.
主要方法:
- 使用易受感染-恢复 (SIR) 框架来构建OA模型.
- 采用普通非线性微分方程,并通过雅可比矩阵和自身值分析平衡点.
- 使用下一代矩阵方法计算复制数.
- 通过使用 MATLAB 的 ODE45 程序 (明确的 Runge-Kutta 算法) 数字地解决了模型.
主要成果:
- 最初的OA模型被发现是不稳定的.
- 一个修改后的OA模型结合了OHS再培训参数,证明了职业事故的减少.
- 数字模拟为事故动态和干预措施的影响提供了洞察力.
结论:
- 开发的OA模型为未来的职业事故估计提供了一个新的方法.
- 加强国家安全政策,特别是改善职业安全培训,有效地减轻了职业事故.
- 该研究强调了持续的OHS培训在预防工作场所事故方面的重要性.
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