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The Frontiers of Society, Science and Technology, 2022, 4(2); doi: 10.25236/FSST.2022.040210.

Analysis of temporal and spatial distribution characteristics and influencing factors of COVID-19 epidemic in 285 cities in China

Author(s)

Yihua He, Chongjing Zhu, Shiyin Chen, Ya Yang

Corresponding Author:
​Yihua He
Affiliation(s)

School of Geographical Sciences, Southwest University, Chongqing, China

Abstract

China is dealing with a serious public health crisis caused by the new coronavirus (COVID-19k). In China, it is essential to investigate the impact of several factors on the diagnosis of COVID-19. Based on data related to the propagation of the COVID-19 epidemic from January 24 to February 28, 2020, this article selected 285 cities in China that have been impacted by the epidemic and analyzed the spatiotemporal distribution characteristics of the epidemic. Additionally, multi-source data such as meteorological environment, social economy, and geographic information were comprehensively considered. On the data, I utilized geographic detectors and random forest algorithms to investigate the most important elements influencing the epidemic's spread. The findings revealed that: (1) The COVID-19 epidemic in China has phase time sequence, spatial aggregation, and distance attenuation features, and the distribution is concentrated in Wuhan; (2) There are two types of COVID-19 infections, non-linear enhancement, and two-factor enhancement. The interaction of natural factors and socioeconomic factors has a stronger impact on the epidemic than the interaction of natural factors. (3) The distance from Wuhan and the number of beds in medical facilities are the two most important elements influencing the epidemic's spread. As a result, timely control of personnel flow, sensible allocation of medical resources, and other actions can successfully stop the epidemic from spreading and have a favorable impact on epidemic prevention and control.

Keywords

coronavirus pandemic; spatiotemporal pattern; influencing factors; geographical detector; random forest

Cite This Paper

Yihua He, Chongjing Zhu, Shiyin Chen, Ya Yang. Analysis of temporal and spatial distribution characteristics and influencing factors of COVID-19 epidemic in 285 cities in China. The Frontiers of Society, Science and Technology (2022) Vol. 4, Issue 2: 52-62. https://doi.org/10.25236/FSST.2022.040210.

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