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暴发事件监测项目，H2020计划）已对谷歌发布的系列PDF报告形式的数据集完成地理配准。这些报告以2020年1月末的基准数据为参照，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
该数据集首批数据于2020年4月2日发布，此后每周进行修订。当前本数据集的地图已采用谷歌发布的CSV格式数据。需注意，本数据集的地图采用前三天的均值进行计算，而谷歌的PDF报告仅使用单日数据，因此本数据集地图中的数值与谷歌PDF中的数值或存在差异。
作者已将多数数据提取为一系列Excel电子表格。每个工作表包含各类场所类别的记录数变化百分比数据，涵盖零售与休闲、食品杂货与药房、公园与海滩、公交站点、工作场所及住宅（对应列F至列K）。第二组列（列L至列P）用于计算各分类数值与对应均值的差值。列A至列E包含地理信息详情，列Q则存储用于关联映射文件的名称。每个日期发布的数据对应单独的工作表（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间的变化量。
另有一张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。我们提供了最新可用日期下，全球（标识为“WD”）及欧洲（标识为“EU”）各流动分类的600 dpi JPEG格式地图，流动分类包括：零售与休闲（“retrec”）、食品杂货与药房（“grocphar”）、公园（“parks”）、公交站点（“transit”）、住宅（“resid”）及工作场所（“work”）。此外还提供了相较前一周的变化量地图（标识为“ch”）。
所有数据提取及后续处理工作均由ERGO（牛津大学环境研究小组，挂靠牛津大学动物学系）代表MOOD H2020项目完成。本数据集将定期更新。如有额外地图需求，可向作者提出申请。