The international community has made significant efforts to flatten the COVID-19 curve,including predicting transmission[1,2],executing unprecedented global lockdowns and social dis-tancing[3,4],promoting the wearing of facemasks and social dis-tancing measures[5],and isolating confirmed cases and contacts[6].Because of the adverse consequences of these lockdown mea-sures[7],many cities have reopened so they can rebuild their economies.However,as mobility has gradually returned towards normal,imported cases from unknown sources have disrupted the recovery situation,and cities are continually at high risk of new waves of infection[8,9]since airborne transmission is the dominant transmission route[10].Unlike studies that focused on the effect of COVID-19 on changes in mobility[11],our study aims to determine the causative relationship and quantify the effects between travel modes and travel destinations and transmission of the pandemic,which is helpful to control the pandemic,especially during the reopening period as mobility progressively returns to normal.

Rui Zhu;Luc Anselin;Michael Batty;Mei-Po Kwan;Min Chen;Wei Luo;Tao Cheng;Che Kang Lim;Paolo Santi;Cheng Cheng;Qiushi Gu;Man Sing Wong;Kai Zhang;Guonian Lü;Carlo Ratti

Department of Land Surveying and Geo-Informatics,the Hong Kong Polytechnic University,Hong Kong,China;Senseable City Laboratory,Future Urban Mobility IRG,Singapore-MIT Alliance for Research and Technology,Singapore 138602,Singapore;Center for Spatial Data Science,Division of the Social Sciences,University of Chicago,Chicago IL 60637,USA;School of Geography Science,Nanjing Normal University,Nanjing 210023,China;Centre for Advanced Spatial Analysis,Faculty of the Built Environment,University College London,London WC1E 6BT,UK;Department of Geography and Resource Management,the Chinese University of Hong Kong,Hong Kong,China;Institute of Space and Earth Information Science,the Chinese University of Hong Kong,Hong Kong,China;Department of Human Geography and Spatial Planning,Utrecht University,Utrecht 3584 CS,Netherlands;State Key Laboratory Cultivation Base of Geographical Environment Evolution,Nanjing 210023,China;Department of Geography,National University of Singapore,Singapore 117570,Singapore;SpaceTimeLab,Department of Civil,Environmental and Geomatic Engineering,University College London,London WC1E 6BT,UK;Department of Clinical Translational Research,Singapore General Hospital,Singapore 169856,Singapore;Division of Clinical Immunology and Transfusion Medicine,Department of Laboratory Medicine,Karolinska Institutet,Stockholm 171 77,Sweden;Senseable City Laboratory,Department of Urban Studies and Planning,Massachusetts Institute of Technology,Cambridge,MA 02139,USA;Istituto di Informatica e Telematica del CNR,Pisa 56124,Italy;Department of System Science,Institute of High Performance Computing,Agency for Science,Technology and Research,Singapore 138632,Singapore;Department of Tourism Studies,School of Humanities,Southeast University,Nanjing 210096,China

科学通报（英文版）

[1]Rui Zhu;Luc Anselin;Michael Batty;Mei-Po Kwan;Min Chen;Wei Luo;Tao Cheng;Che Kang Lim;Paolo Santi;Cheng Cheng;Qiushi Gu;Man Sing Wong;Kai Zhang;Guonian Lü;Carlo Ratti-.The effects of different travel modes and travel destinations on COVID-19 transmission in global cities)[J].科学通报（英文版）,2022(06):588-592

flatten,tancing,facemasks

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