Building an Open Resources Repository for COVID-19 Research

Area of Science:

• Epidemiology
• Data Science
• Geographic Information Systems (GIS)

Background:

• The COVID-19 pandemic necessitates urgent research into its transmissibility, spread, risk factors, and economic effects.
• Reliable data archiving and sharing are crucial for accelerating innovative research efforts against COVID-19.

Purpose of the Study:

• To establish a collaborative and innovative archive of diverse COVID-19-related data resources.
• To process and integrate heterogeneous datasets using GIS for comparability.
• To make all open data permanently accessible via the Harvard Dataverse.

Main Methods:

• Collected diverse data: daily cases, social media, mobility, health facilities, climate, socioeconomic data, research articles, policy, and news.
• Utilized Geographic Information System (GIS) base maps for data processing and integration.
• Published open data to Harvard Dataverse, assigning permanent Digital Object Identifiers (DOIs).

Main Results:

• A comprehensive, integrated COVID-19 dataset was created and made publicly available.
• Preliminary studies using the dataset demonstrated varying spatial transmission patterns across mainland China, Italy, and the United States.
• The data archive facilitates comparative analysis of the pandemic's geographic spread.

Conclusions:

• The established data archive is a valuable resource for COVID-19 research.
• The integration of diverse datasets enhances the understanding of pandemic dynamics.
• Comparative spatial analysis highlights regional differences in COVID-19 transmission.