Data_Mexico_COVID19

Published: 8 August 2020| Version 1 | DOI: 10.17632/mc37xdzw74.1
Contributor:
Jean-François Mas

Description

As spatial analysis can contribute to the understanding of COVID-19 epidemic, we compiled and georeference data for Mexico. Data were compiled from the National Population Council (CONAPO), Google, the National Institute of Statistics and Geography (INEGI), and the Secretary of Health. The data describe the cases of COVID and characteristics of the population, such as distribution, mobility, and prevalence of chronic diseases such as diabetes, hypertension, and obesity. These data were processed to be compatible and georeferenced to a common geographic framework to facilitate spatial analysis in a geographic information system (GIS). The dataset comprises GIS layers (shapefiles), tables (CSV formatted), and R scripts. A complete description will be submitted to the journal Data in Brief (https://www.journals.elsevier.com/data-in-brief/)

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Institutions

Universidad Nacional Autonoma de Mexico

Categories

Geographic Information Systems, Spatial Analysis, Mexico, Comorbidity, Epidemic, COVID-19

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