The US COVID Atlas: A dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic

Marynia Kolak, Xun Li, Qinyun Lin, Ryan Wang, Moksha Menghaney, Stephanie Yang, Vidal Anguiano

Research output: Contribution to journalArticlepeer-review

Abstract

Distributed spatial infrastructures leveraging cloud computing technologies can tackle issues of disparate data sources and address the need for data-driven knowledge discovery and more sophisticated spatial analysis central to the COVID-19 pandemic. We implement a new, open source spatial middleware component (libgeoda) and system design to scale development quickly to effectively meet the need for surveilling county-level metrics in a rapidly changing pandemic landscape. We incorporate, wrangle, and analyze multiple data streams from volunteered and crowdsourced environments to leverage multiple data perspectives. We integrate explorative spatial data analysis (ESDA) and statistical hotspot standards to detect infectious disease clusters in real time, building on decades of research in GIScience and spatial statistics. We scale the computational infrastructure to provide equitable access to data and insights across the entire USA, demanding a basic but high-quality standard of ESDA techniques. Finally, we engage a research coalition and incorporate principles of user-centered design to ground the direction and design of Atlas application development.

Original languageEnglish (US)
Pages (from-to)1741-1765
Number of pages25
JournalTransactions in GIS
Volume25
Issue number4
DOIs
StatePublished - Aug 2021
Externally publishedYes

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

Fingerprint

Dive into the research topics of 'The US COVID Atlas: A dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic'. Together they form a unique fingerprint.

Cite this