Abstract

The 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.

Measurement(s)

Epidemiological Factors • exposure • Demographics • travel history • Quarantine • Symptom Onset • Symptom • Hospitalization • Viral Infection

Technology Type(s)

digital curation • manual coding

Sample Characteristic - Organism

Homo sapiens

Sample Characteristic - Location

China

Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13567553

Details

Title
Mobility, exposure, and epidemiological timelines of COVID-19 infections in China outside Hubei province
Author
Liu Xiao Fan 1   VIAFID ORCID Logo  ; Xiao-Ke, Xu 2 ; Wu, Ye 3 

1  City University of Hong Kong, Web Mining Laboratory, Department of Media and Communication, Hong Kong Special Administrative Region, China (GRID:grid.35030.35) (ISNI:0000 0004 1792 6846) 
2  Dalian Minzu University, College of Information and Communication Engineering, Dalian, China (GRID:grid.440687.9) (ISNI:0000 0000 9927 2735) 
3  Beijing Normal University, Computational Communication Research Center, Zhuhai, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964); Beijing Normal University, School of Journalism and Communication, Beijing, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20524463
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41597-021-00844-8
ProQuest document ID
2486620799
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.