  Over the past few months, the outbreak of Coronavirus disease (COVID-19) has
been expanding over the world. A reliable and accurate dataset of the cases is
vital for scientists to conduct related research and for policy-makers to make
better decisions. We collect the United States COVID-19 daily reported data
from four open sources: the New York Times, the COVID-19 Data Repository by
Johns Hopkins University, the COVID Tracking Project at the Atlantic, and the
USAFacts, then compare the similarities and differences among them. To obtain
reliable data for further analysis, we first examine the cyclical pattern and
the following anomalies, which frequently occur in the reported cases: (1) the
order dependencies violation, (2) the point or period anomalies, and (3) the
issue of reporting delay. To address these detected issues, we propose the
corresponding repairing methods and procedures if corrections are necessary. In
addition, we integrate the COVID-19 reported cases with the county-level
auxiliary information of the local features from official sources, such as
health infrastructure, demographic, socioeconomic, and environmental
information, which are also essential for understanding the spread of the
virus.
