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（即数据科学语境下的疫情事件疾病监测项目，Monitoring Outbreak events for Disease surveillance in a data science context）隶属于欧盟地平线2020（H2020）计划，该项目为谷歌发布的一系列PDF报告中的数据完成了地理参考处理。这些PDF报告围绕相较于2020年1月底基线数据的国家及次国家级人口流动水平展开。相关详情及PDF文件可访问https://www.google.com/covid19/mobility/ 获取。
更多关于这些文件的细节可访问https://www.moodspatialdata.com/humanmobilityforcovid19 查看。
首批数据于2020年4月2日发布，此后每周进行修订。当前地图采用谷歌发布的CSV（逗号分隔值，Comma-Separated Values）数据制作。需注意：地图使用的是前三天数据的平均值，而谷歌PDF报告采用单日数据，因此本项目地图中的数值与谷歌PDF报告的数值可能存在差异。
研究人员已将绝大多数数据提取至一系列Excel电子表格中。每个工作表对应各类场所的记录数量变化百分比数据，涵盖的场所类别包括：零售与休闲、食品杂货与药房、公园与海滩、公交站点、工作场所及居民区（对应工作表F至K列）。第二组列（L至P列）用于计算各分类数值与对应分类均值的差值。A至E列为地理详情信息，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工作表（例如2903、0504等），另有工作表用于计算特定日期间的变化量。
新增的第二个电子表格用于计算2月15日起每日的3日移动平均值，以公历天数进行计数：例如第48天对应2月17日。
欧盟及全球范围的地图展示了上述数据。我们提供了最新发布日期下，全球（标识为"WD"）与欧洲（标识为"EU"）各类流动类别的600dpi JPEG（联合图像专家小组格式）图像，涵盖的流动类别包括：零售与休闲（标识为"retrec"）、食品杂货与药房（标识为"grocphar"）、公园（标识为"parks"）、公交站点（标识为"transit"）、居民区（标识为"resid"）及工作场所（标识为"work"）。同时我们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（牛津大学环境研究小组，Environmental Research Group Oxford，挂靠牛津大学动物学系）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。