MOOD Maps of Google community mobility change during the COVID-19 outbreak

The MOOD project (MOnitoring Outbreak events for Disease surveillance in a data science context. H2020) has geo-referenced the data Google has published as a series of PDF files presenting reports on national and subnational human mobility levels relative to a baseline data of late January 2020. The details and the PDF files can be found at https://www.google.com/covid19/mobility/.<br>More detail on these files can be found at https://www.moodspatialdata.com/humanmobilityforcovid19 <br>The first set of data were released on April 2 2020 and have been revised weekly since then. The maps now utilise the CSV data released by Google. Please note that the maps figures use a mean of the previous three days, while the Google PDFs use a single days data so there will be differences between values in our maps when compare to the Google PDFs.<br>The authors have extracted the majority of these data into a series of excel spreadsheets. Each worksheet provides the data for % change in numbers of records at various types of location categories illustrated by: retail and recreation, grocery and pharmacy, parks and beaches, transit stations, workplaces and residential (columns f to K). A second set of columns calculates the difference of each value from the mean values for each category (columns L to P) Columns A to E contain geographical details. Column Q contains the names used to link to a mapping file.There are separate worksheets for the date of the data from each dated release (e.g. 2903, 0504 etc.) and separate worksheets calculating the changes between specific dates.<br>A second spreadsheet has been added calculating the 3 day moving mean of each day from the 15th of February. Each day is referenced by the Gregorian calendar day count. So day 48 = Feb 17th.<br>The maps (for EU &amp; Global) display these data. We provide 600 dpi jpegs of the Global (“WD”) and European (“EU”) mapped values at the latest date available, for each of the mobility categories: retail and recreation (“retrec”) , grocery and pharmacy (“grocphar”) , parks (“parks”) , transit stations (“transit”), residential (“resid”) and workplaces (“work”). We also provide maps of the changes from the previous week (“ch”).<br>All data extracting and subsequent processing have been carried out by ERGO (Environmental Research Group Oxford, c/o Dept Zoology, University of Oxford) on behalf of the MOOD H2020 project. Data will be periodically updated. Additional maps can be obtained on request to the authors.

MOOD项目（即数据科学场景下的疾病监测暴发事件监测项目，MOnitoring Outbreak events for Disease surveillance in a data science context，隶属于欧盟地平线2020（H2020）科研框架计划）对谷歌发布的一系列PDF报告进行了地理配准（geo-referenced），这些报告呈现了相较于2020年1月末基准数据的国家级及次国家级人类流动性水平。相关PDF文件及细节可访问：https://www.google.com/covid19/mobility/。
该数据集的更多细节可访问：https://www.moodspatialdata.com/humanmobilityforcovid19
首批数据于2020年4月2日发布，此后每周进行修订更新。当前的地图可视化采用了谷歌发布的逗号分隔值（CSV）格式数据。需注意，本项目的地图使用前三日数据的平均值进行绘制，而谷歌的PDF报告仅采用单日数据，因此本项目地图中的数值与谷歌PDF报告中的数值可能存在差异。
作者已将大部分数据整理为一系列Excel电子表格。每个工作表包含各类场所类别的记录数量变化百分比数据，具体类别包括：零售与休闲场所、食品杂货店与药房、公园与海滩、公共交通站点、工作场所以及住宅区域（对应列F至列K）。第二组列（L至P）用于计算各分类数值与对应类别均值的差值。列A至列E包含地理细节信息，列Q则包含用于关联映射文件的名称。每个数据发布日期对应独立的工作表（例如2903、0504等日期编码），同时另有工作表用于计算特定日期之间的变化量。
新增的第二个电子表格用于计算自2月15日起每日的3日移动平均值，每日以公历天数计数，例如第48天对应2月17日。
欧盟（EU）及全球范围的地图可视化展示了上述数据。我们提供了最新日期的全球（标识为"WD"）与欧洲（标识为"EU"）地图的600 dpi JPEG文件，覆盖全部流动性类别：零售与休闲（"retrec"）、食品杂货店与药房（"grocphar"）、公园（"parks"）、公共交通站点（"transit"）、住宅区域（"resid"）以及工作场所（"work"）。此外还提供了相较于前一周变化量的地图（标识为"ch"）。
所有数据提取及后续处理工作均由ERGO（牛津环境研究组，挂靠于牛津大学动物学系）代表MOOD H2020项目完成。数据将定期更新。如有额外地图需求，可向作者提出申请。