Spatiotemporal distribution and trend of COVID-19 in the Yangtze River Delta region of the People’s Republic of China

  • Lei Ye School of Geographic Science, Nantong University, 999 Tongjing Ave, Nantong, Jiangsu, China.
  • Lingqian Hu | School of Architecture and Urban Planning, University of Wisconsin-Milwaukee, Milwaukee, WI, United States.


An outbreak of atypical pneumonia, now called COVID-19 and known to be caused by the novel coronavirus SARS-CoV-2, first detected in Wuhan, Hubei Province of the People’s Republic of China in December 2019 and afterwards rapidly spread worldwide. Wuhan and the Yangtze River Delta (YRD) region implemented first-level public health emergency responses to stop the spread of the virus on January 23rd, 2020. We tracked the geographical gravity centre of the disease and calculated spatial autocorrelation to explore the spatiotemporal patterns of distribution of imported and locally disseminated COVID-19 cases under the emergency-response control measure. We also applied polynomial regression analysis to estimate the trend of the COVID-19 in the YRD region before and after the control activities against the spread of the infection were instituted. The results show that the control measures applied have been effective. And, in the YRD region, areas with a large influx of population flow from Wuhan and Hubei Province had high risks of COVID-19. Therefore, identification of the spatiotemporal trends should be the first step when developing effective policies to manage and control any new epidemic. The results are not only informative locally but also useful for the rest of the world.



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Original Articles
COVID-19, pandemic, China, geographic analysis, gravity center, spatial autocorrelation, polynomial regression
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How to Cite
Ye, L., & Hu, L. (2020). Spatiotemporal distribution and trend of COVID-19 in the Yangtze River Delta region of the People’s Republic of China. Geospatial Health, 15(1).