Authors: Yu Lan*, University of North Carolina - Charlotte, Michael Desjardins, Johns Hopkins Bloomberg School of Public Health, Alexander Hohl, The University of Utah, Eric Delmelle, University of North Carolina at Charlotte
Topics: Medical and Health Geography, Cartography, Geographic Information Science and Systems
Keywords: Geovisualization, COVID-19, space-time pattern, health
Session Type: Virtual Paper
Start / End Time: 3:05 PM / 4:20 PM
Room: Virtual 8
Presentation File: No File Uploaded
Mapping the prevalence and spread of infectious diseases has never been more critical than during the COVID-19 outbreak. A plethora of web-based GIS dashboards have been created incorporating basic GIS functionality, and have served as platforms for rapid data sharing and real-time information for decision making. However, many of those dashboards merely focus on presenting and monitoring cumulative or daily incidence of COVID-19 data, disregarding patterns in both spatial and temporal dimensions. In this paper, we review the usefulness of GIS-based dashboards for mapping the prevalence COVID-19, but also underline missed opportunities that could have been used to reflect the temporal aspect of the disease (cyclicity, seasonality) . We suggest that advanced geovisualization techniques can be used to integrate the temporal component such as 1) an interactive animated bivariate map to show the daily relative risk and the number of days a geographic unit has been in a cluster; 2) an interactive space-time 3D cube to show the death count per unit. We illustrate these approaches on COVID19 cases and death rates at the US county scale from the start of the epidemic. We discuss how each of the visualizations may be understood by the general public and academics familiar with the aforementioned techniques. Finally, we suggest future avenues of research that can facilitate the understanding opportunities that cartographic techniques offer to improve the understanding of COVID-19.