Abstract
AbstractThe 2019 coronavirus disease (COVID-19) is pseudonymously linked to more than 100 million cases in the world as of January 2021. High-quality data are needed but lacking in the understanding of and fighting against COVID-19. We provide a complete and updating hand-coded line-list dataset containing detailed information of the cases in China and outside the epicenter in Hubei province. The data are extracted from public disclosures by local health authorities, starting from January 19. This dataset contains a very rich set of features for the characterization of COVID-19’s epidemiological properties, including individual cases’ demographic information, travel history, potential virus exposure scenario, contacts with known infections, and timelines of symptom onset, quarantine, infection confirmation, and hospitalization. These cases can be considered the baseline COVID-19 transmissibility under extreme mitigation measures, and therefore, a reference for comparative scientific investigation and public policymaking.
Funder
International Social Science Council
Major Project of The National Social Science Fund of China
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability
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