| 引用本文: |
翟元, 张婉玉, 章林, 邹纯朴, 任宏丽.基于中运司天在泉时空特征的肺系疫病发病规律量化印证——以上海地区为例[J].湖南中医药大学学报,2026,46(4):819-828[点击复制] |
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| 基于中运司天在泉时空特征的肺系疫病发病规律量化印证——以上海地区为例 |
| 翟元,张婉玉,章林,邹纯朴,任宏丽 |
| (上海中医药大学, 上海 201203) |
| 摘要: |
| 目的 探讨中运、司天、在泉交临的时空特征对肺系疫病发病规律的宏观调控机制，对五运六气理论进行现代阐释。方法 收集上海地区2005年1月至2024年12月气象数据及同期肺结核、猩红热、麻疹、百日咳、流脑的发病数据，以及2008年1月至2013年12月的甲型H1N1发病数据。将常规气象要素作为基线特征，将理论推演的中运、司天与在泉量化提取为“运气符合度”特征。通过构建随机森林与线性回归联合预测模型进行相互验证，并引入SHAP分析运气特征与常规气象在疫病发病中的非线性耦合机制。结果 融入运气因子后，6种肺系疫病预测模型的拟合性均获提升。同时，SHAP全局分析揭示，运气特征对常规气象要素产生了显著的交互调节效应。结论 上海地区6种肺系疫病的发病规律与中运司天在泉的时空特征之间存在显著的关联性与调控机制。在常规基线模型中引入量化后的运气特征，能更精准地揭示疫病流行规律，为现代肺系疫病的预测与防控提供了理论依据与实证参考。 |
| 关键词: 疫病|肺系|五运六气|随机森林|SHAP分析|线性回归 |
| DOI：10.3969/j.issn.1674-070X.2026.04.024 |
| 投稿时间：2025-10-31 |
| 基金项目:国家中医药管理局中医药古籍挖掘项目(GZY-KJS-2024-08);国家中医药管理局监测统计中心研究课题(2025JCTJE28) |
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| Quantitative validation of incidence patterns of respiratory infectious diseases based on the spatiotemporal characteristics of central movement,celestial controlling, and terrestrial controlling: A case study of Shanghai |
| ZHAI Yuan, ZHANG Wanyu, ZHANG Lin, ZOU Chunpu, REN Hongli |
| (Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China) |
| Abstract: |
| Objective To investigate the macro-regulatory mechanisms of the spatiotemporal characteristics of central movement,celestial controlling, and terrestrial controlling on the incidence patterns of respiratory infectious diseases, and to provide a modern interpretation of the theory of "five movements and six qi(movement-qi)". Methods Meteorological data from Shanghai between January 2005 and December 2024 were collected, along with incidence data for pulmonary tuberculosis, scarlet fever, measles,pertussis, and epidemic cerebrospinal meningitis during the same period, as well as incidence data for influenza A(H1N1) from January 2008 to December 2013. Conventional meteorological variables were used as baseline features, while theoretically derived central movement, celestial controlling, and terrestrial controlling factors were quantitatively extracted as "movement-qi conformity" features. A hybrid predictive framework combining random forest and linear regression models was constructed for mutual validation. SHAP analysis was further introduced to explore the nonlinear coupling mechanisms between movement-qi features and conventional meteorological variables in disease incidence. Results After incorporating movement-qi factors, the goodness-of-fit of predictive models for all six respiratory infectious diseases was improved. SHAP global analysis further revealed significant interactive regulatory effects of movement-qi features on conventional meteorological variables. Conclusion There is a significant association and regulatory mechanism between the incidence patterns of six respiratory infectious diseases in Shanghai and the spatiotemporal characteristics of central movement, celestial controlling, and terrestrial controlling. The incorporation of quantified movement-qi features into conventional baseline models enables more precise identification of epidemic patterns, thereby providing theoretical support and empirical evidence for the prediction and prevention of modern respiratory infectious diseases. |
| Key words: infectious diseases|respiratory system|five movements and six qi|random forest|SHAP analysis|linear regression |
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