4.6 Article

Research on the Spatial Correlation and Spatial Lag of COVID-19 Infection Based on Spatial Analysis

Journal

SUSTAINABILITY
Volume 13, Issue 21, Pages -

Publisher

MDPI
DOI: 10.3390/su132112013

Keywords

COVID-19; spatial autocorrelation; spatial lag model; spatial Durbin model

Funding

  1. Graduate Innovation Fund
  2. Fundamental Research Funds for the Central Universities [3122019143]

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This study aimed to identify the global transmission trend of COVID-19 using spatial correlation and spatial lag analysis. The findings showed that infection was aggregated during a specific period, and COVID-19 patients can infect others with a lag.
COVID-19 has spread throughout the world since the virus was discovered in 2019. Thus, this study aimed to identify the global transmission trend of the COVID-19 from the perspective of the spatial correlation and spatial lag. The research used primary data collected of daily increases in the amount of COVID-19 in 14 countries, confirmed diagnosis, recovered numbers, and deaths. Findings of the Moran index showed that the propagation of infection was aggregated between 9 May and 21 May based on the composite spatial weight matrix. The results from the Lagrange multiplier test indicated the COVID-19 patients can infect others with a lag.

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