在福州探索流感和空气污染之间的时空关系,使用时空加权回归模型
Qingquan Chen1,2, Xiaoyan Zheng1,2, Binglin Xu3
1The Affiliated Fuzhou Center for Disease Control and Prevention of Fujian Medical University, Fuzhou, 350005, China.
Scientific reports
|February 20, 2024
概括
空气污染对流感的传播产生了重大影响,影响因地区和时间而异. 空间和时间加权回归 (STWR) 模型有效地捕捉到这些复杂的动态,以更好地监测传染病.
科学领域:
- 环境健康 环境健康
- 流行病学 流行病学
- 地理空间分析的研究.
背景情况:
- 空气污染是一个日益严重的公共卫生问题,已被确认与流感有联系.
- 了解这种关系的空间和时间变化对于有效的疾病控制至关重要.
研究的目的:
- 研究空气污染对流感的影响的时空空间异质性.
- 确定传染病监测的最佳模式.
主要方法:
- 使用了斯皮尔曼相关性,方差通胀因子 (VIF),普通最小平方 (OLS) 回归,地理加权回归 (GWR) 和空间和时间加权回归 (STWR).
- 模型的性能使用R2,平方余和 (RSS) 和校正的Akaike信息标准 (AICc) 进行评估.
- 动态时间扭曲 (DTW) 和K-medoids算法用于时间序列系数的集群.
主要成果:
- STWR模型表现出优于OLS和GWR的性能,特别是在快速流感爆发期间.
- 二氧化 (NO2) 和颗粒物 (PM10) 对福州东部和西部的流感有相反的影响.
- 在2013年至2019年期间,臭氧 (O3) 对流感强度的影响在西部地区从负转为正,而在东部地区则相反.
结论:
- 空气污染对流感的影响在空间和时间上是异质的.
- STWR模型是分析这些复杂的地理空间关系的宝贵工具.
- 公共卫生战略必须考虑空气污染对流感的影响的时空变化.
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