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Spatial Structure And Climatic Associations With Covid-19 Cases Across The Globe

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Abstract

The study examined the spatial structure and the association between COVID-19 cases and selected climatic variables. Data on cases, deaths, recovery were obtained from the COVID-19 Resources website of the Environmental Systems Research Institute (ESRI). The climatic variables were selected included Land Surface Temperature (LST) and Water Vapour (WV) and collated from the NASA Earth Observations (NEO). Spatial and inferential statistics were used to examine spatial autocorrelation and associations with these variables. Results show that China, Italy, and Iran have the largest number of confirmed cases, the highest recovery (81%) was recorded in China. Confirmed cases have 7 clusters and 2 outlier locations. There are 21 and 17 spatial outliers for recoveries and deaths respectively. There are 2 natural clusters of the incidences and 98.7% of the locations belong to one of the groups. A weak but statistically significant (P

Suggested Citation

  • Lawal, Olanrewaju & Emeka, Anyiam, 2021. "Spatial Structure And Climatic Associations With Covid-19 Cases Across The Globe," Journal of Tourism, Sustainability and Well-being, Cinturs - Research Centre for Tourism, Sustainability and Well-being, University of Algarve, vol. 9(2), pages 75-90.
    • Handle: RePEc:ris:jspord:1030
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    More about this item

    Keywords

    COVID-19; Spatial Clustering; Pandemic; Spatial Autocorrelation; Climatic Variables;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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