IDEAS home Printed from https://ideas.repec.org/a/ris/jspord/1030.html
   My bibliography  Save this article

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

Author

Listed:

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
    as

    Download full text from publisher

    File URL: http://www.cieo.pt/journal/J_2_2021/article1.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ohadike, Don C., 1991. "Diffusion and physiological responses to the influenza pandemic of 1918-19 in Nigeria," Social Science & Medicine, Elsevier, vol. 32(12), pages 1393-1399, January.
    2. Danlin Yu & Yehua Dennis Wei & Changshan Wu, 2007. "Modeling Spatial Dimensions of Housing Prices in Milwaukee, WI," Environment and Planning B, , vol. 34(6), pages 1085-1102, December.
    3. Won Kim, Chong & Phipps, Tim T. & Anselin, Luc, 2003. "Measuring the benefits of air quality improvement: a spatial hedonic approach," Journal of Environmental Economics and Management, Elsevier, vol. 45(1), pages 24-39, January.
    4. Editorial, 2020. "Covid-19 and Climate Change," Journal, Review of Agrarian Studies, vol. 10(1), pages 5-6, January-J.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Löchl, Michael & Axhausen, Kay W., 2010. "Modelling hedonic residential rents for land use and transport simulation while considering spatial effects," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 3(2), pages 39-63.
    2. Yunlong Gong & Peter Boelhouwer & Jan de Haan, 2014. "Spatial Dependence in House Prices: Evidence from China's Interurban Housing Market," ERSA conference papers ersa14p448, European Regional Science Association.
    3. Charlotte Ham & John B. Loomis & Patricia A. Champ, 2015. "Relative Economic Values of Open Space Provided by National Forest and Military Lands to Surrounding Communities," Growth and Change, Wiley Blackwell, vol. 46(1), pages 81-96, March.
    4. Andrea Baranzini & Stefano Carattini & Linda Tesauro, 2021. "Designing Effective and Acceptable Road Pricing Schemes: Evidence from the Geneva Congestion Charge," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 79(3), pages 417-482, July.
    5. S. Wong & C. Yiu & K. Chau, 2013. "Trading Volume-Induced Spatial Autocorrelation in Real Estate Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 46(4), pages 596-608, May.
    6. Robert J. R. Elliott & Ingmar Schumacher & Cees Withagen, 2020. "Suggestions for a Covid-19 Post-Pandemic Research Agenda in Environmental Economics," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(4), pages 1187-1213, August.
    7. Tapsuwan, Sorada & Polyakov, Maksym & Bark, Rosalind & Nolan, Martin, 2015. "Valuing the Barmah–Millewa Forest and in stream river flows: A spatial heteroskedasticity and autocorrelation consistent (SHAC) approach," Ecological Economics, Elsevier, vol. 110(C), pages 98-105.
    8. Patrycja Klusak & Matthew Agarwala & Matt Burke & Moritz Kraemer & Kamiar Mohaddes, 2023. "Rising Temperatures, Falling Ratings: The Effect of Climate Change on Sovereign Creditworthiness," Management Science, INFORMS, vol. 69(12), pages 7468-7491, December.
    9. Marco Helbich & Wolfgang Brunauer & Eric Vaz & Peter Nijkamp, 2014. "Spatial Heterogeneity in Hedonic House Price Models: The Case of Austria," Urban Studies, Urban Studies Journal Limited, vol. 51(2), pages 390-411, February.
    10. Sunak, Yasin & Madlener, Reinhard, 2012. "The Impact of Wind Farms on Property Values: A Geographically Weighted Hedonic Pricing Model," FCN Working Papers 3/2012, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Mar 2013.
    11. Francine Mestrum, 2020. "Universal Social Protection and Health Care as a Social Common," Development, Palgrave Macmillan;Society for International Deveopment, vol. 63(2), pages 238-243, December.
    12. David Klenert & Franziska Funke & Linus Mattauch & Brian O’Callaghan, 2020. "Five Lessons from COVID-19 for Advancing Climate Change Mitigation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(4), pages 751-778, August.
    13. Susan Aaronson, 2021. "Can Trade Agreements Solve the Wicked Problem of Disinformation," Working Papers 2021-12, The George Washington University, Institute for International Economic Policy.
    14. Nguyen, Minh-Hoang & Vuong, Quan-Hoang, 2020. "The third finding concerning a missing cultural value: a bibliometric analysis using the Web of Science," OSF Preprints jbcx3, Center for Open Science.
    15. Gayer Gabrielle & Gilboa Itzhak & Lieberman Offer, 2007. "Rule-Based and Case-Based Reasoning in Housing Prices," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 7(1), pages 1-37, April.
    16. Zeynep Clulow & Michele Ferguson & Peta Ashworth & David Reiner, 2021. "Political ideology and public views of the energy transition in Australia and the UK," Working Papers EPRG2106, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    17. Nestor Goicoechea & Luis María Abadie, 2021. "Optimal Slow Steaming Speed for Container Ships under the EU Emission Trading System," Energies, MDPI, vol. 14(22), pages 1-25, November.
    18. Timothy J. Garrett & Matheus R. Grasselli & Stephen Keen, 2020. "Past production constrains current energy demands: persistent scaling in global energy consumption and implications for climate change mitigation," Papers 2006.03718, arXiv.org.
    19. Luo, Shihua & Hu, Weihao & Liu, Wen & Liu, Zhou & Huang, Qi & Chen, Zhe, 2022. "Flexibility enhancement measures under the COVID-19 pandemic – A preliminary comparative analysis in Denmark, the Netherlands, and Sichuan of China," Energy, Elsevier, vol. 239(PC).
    20. Sanglim Yoo & John E. Wagner, 2016. "A review of the hedonic literatures in environmental amenities from open space: a traditional econometric vs. spatial econometric model," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 20(1), pages 141-166, March.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ris:jspord:1030. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Silvia Fernandes (email available below). General contact details of provider: https://edirc.repec.org/data/ctalgpt.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.