Geospatial Analysis of COVID-19: A Scoping Review

Munazza Fatima, Kara J. O’Keefe, Wenjia Wei, Sana Arshad and Oliver Gruebner
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Munazza Fatima: Department of Geography, The Islamia University of Bahawalpur, Punjab 63100, Pakistan
Kara J. O’Keefe: Department of Epidemiology, Epidemiology, Biostatistics, and Prevention Institute, University of Zurich, CH-8001 Zürich, Switzerland
Wenjia Wei: Department of Epidemiology, Epidemiology, Biostatistics, and Prevention Institute, University of Zurich, CH-8001 Zürich, Switzerland
Sana Arshad: Department of Geography, The Islamia University of Bahawalpur, Punjab 63100, Pakistan
Oliver Gruebner: Department of Epidemiology, Epidemiology, Biostatistics, and Prevention Institute, University of Zurich, CH-8001 Zürich, Switzerland

IJERPH, 2021, vol. 18, issue 5, 1-14

Abstract: The outbreak of SARS-CoV-2 in Wuhan, China in late December 2019 became the harbinger of the COVID-19 pandemic. During the pandemic, geospatial techniques, such as modeling and mapping, have helped in disease pattern detection. Here we provide a synthesis of the techniques and associated findings in relation to COVID-19 and its geographic, environmental, and socio-demographic characteristics, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) methodology for scoping reviews. We searched PubMed for relevant articles and discussed the results separately for three categories: disease mapping, exposure mapping, and spatial epidemiological modeling. The majority of studies were ecological in nature and primarily carried out in China, Brazil, and the USA. The most common spatial methods used were clustering, hotspot analysis, space-time scan statistic, and regression modeling. Researchers used a wide range of spatial and statistical software to apply spatial analysis for the purpose of disease mapping, exposure mapping, and epidemiological modeling. Factors limiting the use of these spatial techniques were the unavailability and bias of COVID-19 data—along with scarcity of fine-scaled demographic, environmental, and socio-economic data—which restrained most of the researchers from exploring causal relationships of potential influencing factors of COVID-19. Our review identified geospatial analysis in COVID-19 research and highlighted current trends and research gaps. Since most of the studies found centered on Asia and the Americas, there is a need for more comparable spatial studies using geographically fine-scaled data in other areas of the world.

Keywords: spatial analysis; COVID-19; disease mapping; exposure mapping; spatial epidemiology; health geography (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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