Visualizing multilayer spatiotemporal epidemiological data with animated geocircles
CoronaViz's unique ability to convey multiple, time-varying, geospatial variables makes it both a valuable addition to interactive COVID-19 dashboards and a platform for empowering experts and the public during future disease outbreaks. CoronaViz is open-source and a live instance is freely hosted at http://coronaviz.umiacs.io.
Authors
- Yunheng Han (ORCID: https://orcid.org/0000-0003-0200-5924)
- John Kastner (ORCID: https://orcid.org/0000-0002-1273-5990)
- Niklas Elmqvist (ORCID: https://orcid.org/0000-0001-5805-5301)
- Ai-Te Kuo (ORCID: https://orcid.org/0000-0002-4206-370X)
- Brian Ondov
- Hanan Samet (ORCID: https://orcid.org/0000-0001-8230-0653)
- Hong Wei (ORCID: https://orcid.org/0000-0001-7838-5455)
- Harsh B Patel
Institutions
- Amazon (United States) (US)
- Aarhus University (DK)
- Yale University (US)
- Meta (United States) (US)
- T. Rowe Price Program for Charitable Giving (US)
- T. Rowe Price Group (United States)
- University of Maryland, College Park (US)
- Auburn University (US)
Publication Details
- Journal
- Journal of the American Medical Informatics Association
- Published
- 2024-08-21
- DOI
- https://doi.org/10.1093/jamia/ocae234
- Citations
- 1
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 0.39
Funders
- National Science Foundation
- National Institutes of Health