杨瑛莹, 詹思怡, 姜棋竞, 傅传喜. 中国258个城市新型冠状病毒肺炎时空分布特征研究[J]. 疾病监测, 2020, 35(11): 977-981. DOI: 10.3784/j.issn.1003-9961.2020.11.005
引用本文: 杨瑛莹, 詹思怡, 姜棋竞, 傅传喜. 中国258个城市新型冠状病毒肺炎时空分布特征研究[J]. 疾病监测, 2020, 35(11): 977-981. DOI: 10.3784/j.issn.1003-9961.2020.11.005
Yang Yingying, Zhan Siyi, Jiang Qijing, Fu Chuanxi. Spatiotemporal characteristics of coronavirus disease 2019 in 258 cities in China[J]. Disease Surveillance, 2020, 35(11): 977-981. DOI: 10.3784/j.issn.1003-9961.2020.11.005
Citation: Yang Yingying, Zhan Siyi, Jiang Qijing, Fu Chuanxi. Spatiotemporal characteristics of coronavirus disease 2019 in 258 cities in China[J]. Disease Surveillance, 2020, 35(11): 977-981. DOI: 10.3784/j.issn.1003-9961.2020.11.005

中国258个城市新型冠状病毒肺炎时空分布特征研究

Spatiotemporal characteristics of coronavirus disease 2019 in 258 cities in China

  • 摘要:
      目的  分析中国新型冠状病毒肺炎(COVID-19)的时空分布特征及相关因素,为COVID-19防控提供依据。
      方法  基于2020年1月21日至3月23日中国258个城市的COVID-19发病率、人口流动(湖北省武汉市迁入)、社会人口学、地理信息数据,进行空间自相关和热点分析,揭示COVID-19流行的空间异质性,识别热点区域。 利用地理加权回归模型结合线性回归模型,探讨空间异质性的相关因素。
      结果  2020年1月21日至3月23日,258个城市累计报告29 789例COVID-19病例,COVID-19流行总体呈空间聚集性(Moran's I = 0.436,Z=25.363,P<0.001)。 各地的百度迁徙指数(武汉市迁入)与COVID-19发病关联有统计学意义(t=14.550,P<0.001),百度迁徙指数表现出正向效应(β: 0.564 ~ 0.565)。
      结论  中国COVID-19流行存在空间异质性,武汉市人口迁入多的地区报告发病水平更高。 对新发传染病的时空特征理解有助于疾病流行的早期预警和控制。

     

    Abstract:
      Objective  To explore the spatiotemporal characteristics of coronavirus disease 2019 (COVID-19) in China and related factors, and provide evidence for COVID-19 prevention and control.
      Methods  Based on the information about COVID-19 incidence, population migration from Wuhan of Hubei, socio-demography and geography in 258 prefecture-level cities in China from January 21 to March 23, 2020, a spatial autocorrelation analysis and a hot spot analysis were conducted to explore the spatial heterogeneity and identify the hot spots of COVID-19 epidemic. The geographically weighted regression (GWR) model combined with linear regression model was used to identify the related factors for spatial heterogeneity.
      Results  During January 21 to March 23, 2020, a total of 29 789 COVID-19 cases were reported in 258 cities. The overall incidence of COVID-19 showed spatial clustering (Moran's I=0.436, Z=25.363, P<0.001). The Baidu migration index (from Wuhan) was statistically related to COVID-19 incidence at city level (t=14.550, P<0.001), showing positive effect ( β: 0.564–0.565).
      Conclusion  Spatial heterogeneity was noted in COVID-19 epidemic in China. Cities with more migration from Wuhan were more likely to report higher COVID-19 incidence. Understanding spatiotemporal characteristics of emerging infectious diseases is helpful to the early warning and control of the epidemic.

     

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