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The Role of Remote Sensing and Geospatial Analysis for Understanding COVID-19 Population Severity: A Systematic Review

Author

Listed:
  • Butros M. Dahu

    (Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
    Department of Health Management and Informatics, University of Missouri, Columbia, MO 65211, USA)

  • Khuder Alaboud

    (Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
    NextGen Biomedical Informatics Center, University of Missouri, Columbia, MO 65211, USA)

  • Avis Anya Nowbuth

    (Pan African Organization for Health Education and Research (POHER), Manchester, MO 63011, USA)

  • Hunter M. Puckett

    (Department of Health Management and Informatics, University of Missouri, Columbia, MO 65211, USA)

  • Grant J. Scott

    (Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
    Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA)

  • Lincoln R. Sheets

    (Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
    Department of Health Management and Informatics, University of Missouri, Columbia, MO 65211, USA)

Abstract

Remote sensing (RS), satellite imaging (SI), and geospatial analysis have established themselves as extremely useful and very diverse domains for research associated with space, spatio-temporal components, and geography. We evaluated in this review the existing evidence on the application of those geospatial techniques, tools, and methods in the coronavirus pandemic. We reviewed and retrieved nine research studies that directly used geospatial techniques, remote sensing, or satellite imaging as part of their research analysis. Articles included studies from Europe, Somalia, the USA, Indonesia, Iran, Ecuador, China, and India. Two papers used only satellite imaging data, three papers used remote sensing, three papers used a combination of both satellite imaging and remote sensing. One paper mentioned the use of spatiotemporal data. Many studies used reports from healthcare facilities and geospatial agencies to collect the type of data. The aim of this review was to show the use of remote sensing, satellite imaging, and geospatial data in defining features and relationships that are related to the spread and mortality rate of COVID-19 around the world. This review should ensure that these innovations and technologies are instantly available to assist decision-making and robust scientific research that will improve the population health diseases outcomes around the globe.

Suggested Citation

  • Butros M. Dahu & Khuder Alaboud & Avis Anya Nowbuth & Hunter M. Puckett & Grant J. Scott & Lincoln R. Sheets, 2023. "The Role of Remote Sensing and Geospatial Analysis for Understanding COVID-19 Population Severity: A Systematic Review," IJERPH, MDPI, vol. 20(5), pages 1-15, February.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:5:p:4298-:d:1083097
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    References listed on IDEAS

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    1. B. Tellman & J. A. Sullivan & C. Kuhn & A. J. Kettner & C. S. Doyle & G. R. Brakenridge & T. A. Erickson & D. A. Slayback, 2021. "Satellite imaging reveals increased proportion of population exposed to floods," Nature, Nature, vol. 596(7870), pages 80-86, August.
    2. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
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