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) 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（MOOD，即数据科学场景下的疾病监测暴发事件监测项目，H2020资助项目）已对谷歌发布的一系列PDF报告中的数据完成地理配准，此类报告以2020年1月底的基准数据为参照，展示国家及次国家级的人类出行流动水平。相关详情及PDF文件可访问https://www.google.com/covid19/mobility/。更多文件细节可访问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。当前的可视化地图已采用谷歌发布的CSV格式数据。需注意：本项目地图使用前三日的平均值进行绘制，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。
研究团队已将绝大多数此类数据提取至多个Excel电子表格中。每个工作表对应一类场所类别的记录数量变化百分比，涵盖零售与娱乐、食品杂货与药房、公园与海滩、公共交通站点、工作场所及住宅区域（对应工作表的F至K列）。第二组列（L至P列）用于计算各类别数值与对应平均值的差值。A至E列包含地理信息详情，Q列则为用于关联映射文件的标识名称。每个数据发布日期对应独立的工作表（例如采用2903、0504等格式的日期标识），同时另有工作表用于计算特定日期之间的数值变化。
另有第二个电子表格用于计算自2月15日起的每日3日移动平均值，每日以公历天数计数标识，例如第48天对应2月17日。
针对欧盟及全球范围的可视化地图已展示上述数据。我们提供了最新日期的全球（标识为“WD”）及欧洲（标识为“EU”）各类流动类别的600dpi JPEG格式地图，流动类别包括：零售与娱乐（retrec）、食品杂货与药房（grocphar）、公园（parks）、公共交通站点（transit）、住宅区域（resid）及工作场所（work）。此外我们还提供了相较于前一周的变化情况地图（标识为“ch”）。
所有数据提取及后续处理工作均由牛津大学环境研究小组（ERGO）代表MOOD H2020项目完成。本数据集将定期更新。如需获取额外地图可联系本文作者。