Geospatial Analysis of COVID-19: A Scoping Review

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.

What most influences severity and death of COVID-19 patients in Brazil? Is it clinical, social, or demographic factors? An observational study

“…The finding of increased mortality indicate that efforts aimed at the management of chronic conditions and the care of the elderly should be the focus of public policies towards COVID-19 [30], for areas with high and low socioeconomic status.…”

Examining second-order impacts of COVID-19 in urban areas

“…While the COVID-19 virus has catalysed an international research effort to create a vaccine in record time (Yong 2020), it also provides an opportunity to facilitate global research using geospatial analyses (Ahasan et al 2020;Fatima et al 2021;Helbich, Browning, and Kwan 2021;Yang et al 2020). Ahasan et al (2020) conduct a systematic review of emerging research of geographic information systems (GIS) and geospatial analyses of COVID-19 across thematic groups with an emphasis on public health and first-order impacts (e.g.…”

The Use of GIS Technology to Optimize COVID-19 Vaccine Distribution: A Case Study of the City of Warsaw, Poland

“…In the case of the COVID-19 pandemic, this technology was used extensively to understand the spatiotemporal dynamics of COVID-19. The analyses conducted until now have mainly examined spatial distribution and analysis of COVID-19 cases and/or deaths in relation to geographic area, age, sex, health, living conditions, socio-economic and environmental variables [ 36 , 37 ], as well as spatiotemporal COVID-19 patterns and their changes [ 38 , 39 ], early forecasting of the potential risk zones of COVID-19 [ 40 ], and risk modelling of COVID-19 infections [ 21 , 41 , 42 , 43 ]. However, the use of spatial analysis may also be useful in optimizing the location of vaccination sites and the distribution of vaccines.…”