Spatio-temporal dataset of COVID-19 outbreak in Mexico

被引：4

作者：

Mas, Jean-Francois ^{[1
]}

机构：

[1] Univ Nacl Autonoma Mexico, Lab Anal Espacial, Ctr Invest Geog Ambiental, Antigua Carretera Patzcuaro 8701, Morelia 58190, Michoacan, Mexico

来源：

DATA IN BRIEF | 2021年 / 35卷

关键词：

COVID-19; Chronic diseases; Epidemic; GIS; Mobility; Municipalities; Public health;

D O I：

10.1016/j.dib.2021.106843

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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 geo-referenced to a common geographic framework to facilitate spatial analysis in a geographic information system (GIS). (C) 2021 Published by Elsevier Inc.

引用

页数：5