A Multiscale Geospatial Dataset and an Interactive Visualization Dashboard for Computational Epidemiology and Open Scientific Research

Muhammad Usman, Honglu Zhou, Seonghyeon Moon, Xun Zhang, Petros Faloutsos, Mubbasir Kapadia

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The coronavirus disease (COVID-19) continued to strike as a highly infectious and fast-spreading disease in 2020 and 2021. As the research community actively responded to this pandemic, we saw the release of many COVID-19-related datasets and visualization dashboards. However, existing resources are insufficient to support multiscale and multifaceted modeling or simulation, which is suggested to be important by the computational epidemiology literature. This work presents a curated multiscale geospatial dataset with an interactive visualization dashboard under the context of COVID-19. This open dataset will allow researchers to conduct numerous projects or analyses relating to COVID-19 or simply geospatial-related scientific studies. The interactive visualization platform enables users to visualize the spread of the disease at different scales (e.g., country level to individual neighborhoods), and allows users to interact with the policies enforced at these scales (e.g., the closure of borders and lockdowns) to observe their impacts on the epidemiology.

Original languageEnglish
Pages (from-to)39-52
Number of pages14
JournalIEEE Computer Graphics and Applications
Volume43
Issue number1
DOIs
StatePublished - 1 Jan 2023

Bibliographical note

Publisher Copyright:
© 1981-2012 IEEE.

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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