Spatio-temporal dataset of COVID-19 outbreak in Mexico
Jean‐François Mas
Abstract
Our understanding of how COVID-19 spreads over a territory needs to be improved. For example, the evaluation of disease spatiotemporal distribution and its association with other characteristics can help identify covariates, model the behavior of the epidemic, and provide useful information for decision making. 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).