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（即数据科学框架下的疾病暴发监测项目，全称MOnitoring Outbreak Events for Disease Surveillance in a Data Science Context，为H2020计划资助项目）已对谷歌发布的相关数据进行地理编码：谷歌曾发布一系列PDF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员流动性水平。详细信息及PDF文件可访问https://www.google.com/covid19/mobility/。
更多相关文件细节可访问https://www.moodspatialdata.com/humanmobilityforcovid19。
该数据集首批于2020年4月2日发布，此后每周进行修订。当前地图产品采用谷歌发布的CSV格式数据。需注意：地图产品使用的是前三日的均值数据，而谷歌PDF文档采用单日数据，因此本项目地图与谷歌PDF文档中的数值存在差异。
项目作者已将多数数据整理为若干Excel电子表格。每个工作表对应各类场所的记录数量变化百分比，涵盖的场所类别包括：零售与娱乐场所、食品杂货与药店、公园与海滩、公共交通站点、工作场所及居民区（对应表格F至K列）。第二组列（L至P列）用于计算各分类数值与对应均值的差值。A至E列为地理信息字段，Q列为用于关联映射文件的名称标识。每个数据发布日期对应独立工作表（例如2903、0504等日期编码格式），另有工作表用于计算特定日期间的流动性变化量。
新增的第二份电子表格用于计算2月15日起每日的3日移动平均值，以公历日计数作为每日标识，例如第48天对应2月17日。
面向欧盟及全球范围的地图产品展示了上述数据。我们提供了最新日期的全球（代号"WD"）与欧洲（代号"EU"）区域的各流动性分类的600dpi JPEG格式地图，涵盖的流动性分类包括：零售与娱乐（代号"retrec"）、食品杂货与药店（代号"grocphar"）、公园（代号"parks"）、公共交通站点（代号"transit"）、居民区（代号"resid"）及工作场所（代号"work"）。此外还提供了较前一周变化量的地图（代号"ch"）。
所有数据提取及后续处理工作均由ERGO（牛津环境研究小组，Environmental Research Group Oxford）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获取。