Data_Mexico_COVID19

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 was published in the journal Data in Brief (https://doi.org/10.1016/j.dib.2021.106843). From version 4, population data from the 2020 INEGI Population census are incorporated in the data. COVID data was updated to data available on March 23, 2021.

鉴于空间分析有助于深化对新型冠状病毒肺炎（COVID-19）疫情的认识，本研究整理并地理配准了墨西哥相关数据集。数据来源于墨西哥全国人口委员会（National Population Council, CONAPO）、谷歌（Google）、墨西哥国家统计与地理研究所（National Institute of Statistics and Geography, INEGI）及墨西哥卫生部（Secretary of Health）。该数据集涵盖COVID-19病例信息与人口特征指标，包括人口分布、流动情况以及糖尿病、高血压、肥胖等慢性病的患病率。所有数据均经过兼容化处理，并统一地理配准至通用地理框架，以支持在地理信息系统（GIS）中开展空间分析。本数据集包含GIS图层（shapefiles）、CSV格式表格及R脚本文件。该数据集的完整说明已发表于《数据简报（Data in Brief）》期刊（https://doi.org/10.1016/j.dib.2021.106843）。自第4版起，数据集纳入了2020年墨西哥国家统计与地理研究所人口普查的人口数据；COVID-19病例数据已更新至2021年3月23日的可用数据。