COVID-19 Open-Data a global-scale spatially granular meta-dataset for coronavirus disease.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
12 04 2022
12 04 2022
Historique:
received:
28
04
2021
accepted:
28
02
2022
entrez:
13
4
2022
pubmed:
14
4
2022
medline:
15
4
2022
Statut:
epublish
Résumé
This paper introduces the COVID-19 Open Dataset (COD), available at goo.gle/covid-19-open-data . A static copy is of the dataset is also available at https://doi.org/10.6084/m9.figshare.c.5399355 . This is a very large "meta-dataset" of COVID-related data, containing epidemiological information, from 22,579 unique locations within 232 different countries and independent territories. For 62 of these countries we have state-level data, and for 23 of these countries we have county-level data. For 15 countries, COD includes cases and deaths stratified by age or sex. COD also contains information on hospitalizations, vaccinations, and other relevant factors such as mobility, non-pharmaceutical interventions and static demographic attributes. Each location is tagged with a unique identifier so that these different types of information can be easily combined. The data is automatically extracted from 121 different authoritative sources, using scalable open source software. This paper describes the format and construction of the dataset, and includes a preliminary statistical analysis of its content, revealing some interesting patterns.
Identifiants
pubmed: 35413965
doi: 10.1038/s41597-022-01263-z
pii: 10.1038/s41597-022-01263-z
pmc: PMC9005692
doi:
Types de publication
Dataset
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
162Informations de copyright
© 2022. The Author(s).
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