A Comprehensive COVID-19 Database for the United States

The diversity in responses to and conditions resulting from the COVID-19 pandemic in the United States has provided rich data for researchers to study, especially as the pandemic continues to progress. With more than a full year of data available in different regions and at different granularities, methods of analysis requiring larger datasets are now worth examining or refining. Furthermore, as the United States seeks to move away from national and state-wide policies into approaches focused on individual communities, open data must be provided at both the state and county levels. In this paper, a comprehensive database encompassing COVID-19 data and a large body of related data is proposed. The database includes data on cases and deaths, testing, mobility, demographics, weather, and more at both the US state and county levels. The system was implemented using the Python framework Django and the high-performance RDBMS PostgreSQL. A data-processing pipeline was implemented using the asynchronous task library Celery to gather and clean data from various verified sources. This database has been used to build a web application for concise reporting and an open API for public access to the data. A reference web application using the API is currently available at www.bigdatacovid.com, and the API is available at www.bigdatacovid.com/api/v1, with API documentation available on the website.