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（数据科学背景下的疫情事件监测，全称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）已对谷歌发布的一系列PDF报告数据完成地理配准处理，这些报告以2020年1月下旬的基准数据为参照，展示了国家及次国家层面的人员流动水平。相关数据及PDF报告可访问：https://www.google.com/covid19/mobility/。
有关这些文件的更多详细信息可访问：https://www.moodspatialdata.com/humanmobilityforcovid19。
首批数据于2020年4月2日发布，此后每周进行一次修订。当前地图采用谷歌发布的逗号分隔值（CSV）数据进行绘制。请注意，本数据集的地图使用前三日的均值进行计算，而谷歌原始PDF报告仅采用单日数据，因此本数据集地图中的数值与谷歌PDF报告中的数值可能存在差异。
项目团队已将大部分数据提取为一系列Excel电子表格。每个工作表涵盖不同场所类别的记录数变化百分比数据，具体包括零售与娱乐、食品杂货店与药房、公园与海滩、公交站点、工作场所及住宅场所（对应表格F至K列）。第二组列用于计算各场所类别中各数值与对应类别均值的差值（对应L至P列）。A至E列包含地理信息，Q列则包含用于关联映射文件的名称。每个数据发布日期对应单独的工作表（例如采用2903、0504等格式），另有单独的工作表用于计算特定日期之间的变化量。
新增了第二份电子表格，用于计算2月15日起每日的3日移动均值。每日以公历（Gregorian calendar）天数计数进行标识，例如第48天对应2月17日。
欧盟（EU）及全球范围的地图可展示上述数据。本数据集提供了当前最新日期下，全球（标识为"WD"）与欧洲（标识为"EU"）各流动类别对应的600dpi的JPEG格式图像，涵盖的流动类别包括：零售与娱乐（retrec）、食品杂货店与药房（grocphar）、公园（parks）、公交站点（transit）、住宅场所（resid）及工作场所（work）。此外还提供了较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，如需额外地图可联系作者索取。