在中国大陆,对影响人类结核病风险的空气污染进行预测建模
Boli Qin1, Rongqing He1, Xiaopeng Qin1
1The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, People's Republic of China.
Scientific reports
|July 2, 2025
概括
空气污染与中国的结核病 (TB) 率有显著的相关性. 机器学习模型显示,空气质量数据可以预测结核病发病率和死亡率,有助于公共卫生战略.
科学领域:
- 环境科学环境科学
- 公共卫生 公共卫生
- 流行病学 流行病学
背景情况:
- 空气污染是一个全球性的健康问题.
- 结核病 (TB) 仍然是一个重大的公共卫生挑战,特别是在中国.
- 了解环境对疾病的影响对于有效控制至关重要.
研究的目的:
- 调查空气污染与中国结核病发病率和死亡率之间的相关性.
- 利用空气质量数据开发基于机器学习的结核病发病率预测模型.
- 通过将环境因素纳入结核病控制,为公共卫生战略提供信息.
主要方法:
- 收集了结核病发病率/死亡率和六个空气污染指标 (2013-2020) 的数据.
- 采用了六种算法的回归模型,包括随机森林 (RF).
- 利用夏普利添加式解释 (SHAP) 来进行模型解释和季节性自回归集成移动平均 (SARIMA) 来进行预测.
主要成果:
- 在空气污染指标和结核病率之间发现了显著的相关性.
- 射频模型在预测结核病发病率和死亡率方面表现优异.
- 10个月的滞后期被认为是空气污染对结核病影响的最佳时间.
结论:
- 空气污染数据可以有效预测结核病发病率和死亡率.
- 整合环境数据和人工智能对于开发强大的结核病控制策略至关重要.
- 环境监测应该是针对传染病的公共卫生倡议的关键组成部分.
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