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A worldwide epidemiological database for COVID-19 at fine-grained spatial resolution.
Guidotti, Emanuele.
Afiliación
  • Guidotti E; University of Neuchâtel, Institute of Financial Analysis, Neuchâtel, 2000, Switzerland. emanuele.guidotti@unine.ch.
Sci Data ; 9(1): 112, 2022 03 29.
Article en En | MEDLINE | ID: mdl-35351921
ABSTRACT
This database provides the daily time-series of COVID-19 cases, deaths, recovered people, tests, vaccinations, and hospitalizations, for more than 230 countries, 760 regions, and 12,000 lower-level administrative divisions. The geographical entities are associated with identifiers to match with hydrometeorological, geospatial, and mobility data. The database includes policy measures at the national and, when available, sub-national levels. The data acquisition pipeline is open-source and fully automated. As most governments revise the data retrospectively, the database always updates the complete time-series to mirror the original source. Vintage data, immutable snapshots of the data taken each day, are provided to ensure research reproducibility. The latest data are updated on an hourly basis, and the vintage data are available since April 14, 2020. All the data are available in CSV files or SQLite format. By unifying the access to the data, this work makes it possible to study the pandemic on a global scale with high resolution, taking into account within-country variations, nonpharmaceutical interventions, and environmental and exogenous variables.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Sci Data Año: 2022 Tipo del documento: Article País de afiliación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Sci Data Año: 2022 Tipo del documento: Article País de afiliación: Suiza