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（数据科学语境下疾病监测相关疫情事件监测项目，H2020计划）对谷歌发布的一系列PDF报告数据进行了地理配准，此类报告以2020年1月末的基准数据为参照，展示了国家级及次国家级的人员流动水平。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。
首批数据于2020年4月2日发布，此后每周进行修订。当前的地图可视化采用了谷歌发布的CSV（Comma-Separated Values）数据。需注意：本项目的地图使用前三天的均值数据，而谷歌的PDF报告采用单日数据，因此本项目地图中的数值与谷歌PDF报告中的数值存在差异。
作者团队已将绝大多数此类数据提取至一系列Excel电子表格中。每个工作表对应一类地点类别的记录数量相较于基准值的变化百分比，涵盖的类别包括：零售与娱乐场所、食品杂货店与药房、公园与海滩、公交站点、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总体均值的差值。A至E列为地理信息详情，Q列为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（例如采用2903、0504等格式的日期编码），另有独立工作表用于计算特定日期间的变化量。
另有一个电子表格用于计算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。
针对欧盟（EU）及全球范围的地图展示了此类数据。我们为最新可用日期的各流动类别提供了600dpi的JPEG（联合图像专家小组格式）格式地图文件：全球范围（标识为"WD"）及欧洲范围（标识为"EU"），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，Environmental Research Group Oxford）代表MOOD H2020项目完成。数据将定期更新。如需获取额外地图可联系作者团队。