Spatial epidemic dynamics of the COVID-19 outbreak in China. (May 2020)

• Record Type: Journal Article
• Authors: Kang, Dayun; Choi, Hyunho; Kim, Jong-Hun; Choi, Jungsoon
• Is Part Of: International journal of infectious diseases. Volume 94(2020)
• Page Start: 96
• Page End: 102
• Publication Date: 2020-05
• Subjects: COVID-19 -- Spatial autocorrelation -- Spatial analysis -- China; Communicable diseases -- Periodicals; Communicable Diseases -- Periodicals; Communicable diseases; Periodicals; Electronic journals; 616.9
• DOI: 10.1016/j.ijid.2020.03.076
• Languages: English
• ISSNs: 1201-9712

Abstract

Highlights: Spatial dynamics of the COVID-2019 in mainland China were examined. Moran's I spatial statistic was used with different types of neighbourhoods. Population-related and medical care-related information were considered. There is a need for spatial analysis to prevent the spread of infectious diseases. Abstract: Background: On 31 December 2019 an outbreak of COVID-19 in Wuhan, China, was reported. The outbreak spread rapidly to other Chinese cities and multiple countries. This study described the spatio-temporal pattern and measured the spatial association of the early stages of the COVID-19 epidemic in mainland China from 16 January–06 February 2020. Methods: This study explored the spatial epidemic dynamics of COVID-19 in mainland China. Moran's I spatial statistic with various definitions of neighbours was used to conduct a test to determine whether a spatial association of the COVID-19 infections existed. Results: The spatial spread of the COVID-19 pandemic in China was observed. The results showed that most of the models, except medical-care-based connection models, indicated a significant spatial association of COVID-19 infections from around 22 January 2020. Conclusions: Spatial analysis is of great help in understanding the spread of infectious diseases, and spatial association was the key to the spatial spread during the early stages of the COVID-19 pandemic in mainland China.