Non-compulsory measures sufficiently reduced human mobility in Tokyo during the COVID-19 epidemic

While large scale mobility data has become a popular tool to monitor the mobility patterns during the COVID-19 pandemic, the impacts of non-compulsory measures in Tokyo, Japan on human mobility patterns has been under-studied. Here, we analyze the temporal changes in human mobility behavior, social...

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Veröffentlicht in:	Scientific reports Jg. 10; H. 1; S. 18053 - 9
Hauptverfasser:	Yabe, Takahiro, Tsubouchi, Kota, Fujiwara, Naoya, Wada, Takayuki, Sekimoto, Yoshihide, Ukkusuri, Satish V.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 22.10.2020 Nature Publishing Group Nature Portfolio
Schlagworte:	639/166 692/699 704/844/1759 Behavior Betacoronavirus - isolation & purification Cell Phone Use - statistics & numerical data Coronavirus Infections - epidemiology Coronavirus Infections - pathology Coronavirus Infections - virology Coronaviruses COVID-19 Humanities and Social Sciences Humans Mobility Movement - physiology multidisciplinary Pandemics Pneumonia, Viral - epidemiology Pneumonia, Viral - pathology Pneumonia, Viral - virology SARS-CoV-2 Science Science (multidisciplinary) Social behavior Time Factors Tokyo - epidemiology Tokyo
ISSN:	2045-2322, 2045-2322
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Abstract	While large scale mobility data has become a popular tool to monitor the mobility patterns during the COVID-19 pandemic, the impacts of non-compulsory measures in Tokyo, Japan on human mobility patterns has been under-studied. Here, we analyze the temporal changes in human mobility behavior, social contact rates, and their correlations with the transmissibility of COVID-19, using mobility data collected from more than 200K anonymized mobile phone users in Tokyo. The analysis concludes that by April 15th (1 week into state of emergency), human mobility behavior decreased by around 50%, resulting in a 70% reduction of social contacts in Tokyo, showing the strong relationships with non-compulsory measures. Furthermore, the reduction in data-driven human mobility metrics showed correlation with the decrease in estimated effective reproduction number of COVID-19 in Tokyo. Such empirical insights could inform policy makers on deciding sufficient levels of mobility reduction to contain the disease.
AbstractList	While large scale mobility data has become a popular tool to monitor the mobility patterns during the COVID-19 pandemic, the impacts of non-compulsory measures in Tokyo, Japan on human mobility patterns has been under-studied. Here, we analyze the temporal changes in human mobility behavior, social contact rates, and their correlations with the transmissibility of COVID-19, using mobility data collected from more than 200K anonymized mobile phone users in Tokyo. The analysis concludes that by April 15th (1 week into state of emergency), human mobility behavior decreased by around 50%, resulting in a 70% reduction of social contacts in Tokyo, showing the strong relationships with non-compulsory measures. Furthermore, the reduction in data-driven human mobility metrics showed correlation with the decrease in estimated effective reproduction number of COVID-19 in Tokyo. Such empirical insights could inform policy makers on deciding sufficient levels of mobility reduction to contain the disease. Abstract While large scale mobility data has become a popular tool to monitor the mobility patterns during the COVID-19 pandemic, the impacts of non-compulsory measures in Tokyo, Japan on human mobility patterns has been under-studied. Here, we analyze the temporal changes in human mobility behavior, social contact rates, and their correlations with the transmissibility of COVID-19, using mobility data collected from more than 200K anonymized mobile phone users in Tokyo. The analysis concludes that by April 15th (1 week into state of emergency), human mobility behavior decreased by around 50%, resulting in a 70% reduction of social contacts in Tokyo, showing the strong relationships with non-compulsory measures. Furthermore, the reduction in data-driven human mobility metrics showed correlation with the decrease in estimated effective reproduction number of COVID-19 in Tokyo. Such empirical insights could inform policy makers on deciding sufficient levels of mobility reduction to contain the disease. While large scale mobility data has become a popular tool to monitor the mobility patterns during the COVID-19 pandemic, the impacts of non-compulsory measures in Tokyo, Japan on human mobility patterns has been under-studied. Here, we analyze the temporal changes in human mobility behavior, social contact rates, and their correlations with the transmissibility of COVID-19, using mobility data collected from more than 200K anonymized mobile phone users in Tokyo. The analysis concludes that by April 15th (1 week into state of emergency), human mobility behavior decreased by around 50%, resulting in a 70% reduction of social contacts in Tokyo, showing the strong relationships with non-compulsory measures. Furthermore, the reduction in data-driven human mobility metrics showed correlation with the decrease in estimated effective reproduction number of COVID-19 in Tokyo. Such empirical insights could inform policy makers on deciding sufficient levels of mobility reduction to contain the disease.While large scale mobility data has become a popular tool to monitor the mobility patterns during the COVID-19 pandemic, the impacts of non-compulsory measures in Tokyo, Japan on human mobility patterns has been under-studied. Here, we analyze the temporal changes in human mobility behavior, social contact rates, and their correlations with the transmissibility of COVID-19, using mobility data collected from more than 200K anonymized mobile phone users in Tokyo. The analysis concludes that by April 15th (1 week into state of emergency), human mobility behavior decreased by around 50%, resulting in a 70% reduction of social contacts in Tokyo, showing the strong relationships with non-compulsory measures. Furthermore, the reduction in data-driven human mobility metrics showed correlation with the decrease in estimated effective reproduction number of COVID-19 in Tokyo. Such empirical insights could inform policy makers on deciding sufficient levels of mobility reduction to contain the disease. While large scale mobility data has become a popular tool to monitor the mobility patterns during the COVID-19 pandemic, the impacts of non-compulsory measures in Tokyo, Japan on human mobility patterns has been under-studied. Here, we analyze the temporal changes in human mobility behavior, social contact rates, and their correlations with the transmissibility of COVID-19, using mobility data collected from more than 200K anonymized mobile phone users in Tokyo. The analysis concludes that by April 15th (1 week into state of emergency), human mobility behavior decreased by around 50%, resulting in a 70% reduction of social contacts in Tokyo, showing the strong relationships with non-compulsory measures. Furthermore, the reduction in data-driven human mobility metrics showed correlation with the decrease in estimated effective reproduction number of COVID-19 in Tokyo. Such empirical insights could inform policy makers on deciding sufficient levels of mobility reduction to contain the disease.
ArticleNumber	18053
Author	Wada, Takayuki Sekimoto, Yoshihide Tsubouchi, Kota Yabe, Takahiro Fujiwara, Naoya Ukkusuri, Satish V.
Author_xml	– sequence: 1 givenname: Takahiro orcidid: 0000-0001-8967-1967 surname: Yabe fullname: Yabe, Takahiro organization: Lyles School of Civil Engineering, Purdue University – sequence: 2 givenname: Kota surname: Tsubouchi fullname: Tsubouchi, Kota organization: Yahoo Japan Corporation – sequence: 3 givenname: Naoya orcidid: 0000-0002-7753-4698 surname: Fujiwara fullname: Fujiwara, Naoya organization: Graduate School of Information Sciences, Tohoku University, Institute of Industrial Science, The University of Tokyo, Center for Spatial Information Science, The University of Tokyo – sequence: 4 givenname: Takayuki surname: Wada fullname: Wada, Takayuki organization: Graduate School of Human Life Science, Osaka City University – sequence: 5 givenname: Yoshihide surname: Sekimoto fullname: Sekimoto, Yoshihide organization: Institute of Industrial Science, The University of Tokyo – sequence: 6 givenname: Satish V. orcidid: 0000-0001-8754-9925 surname: Ukkusuri fullname: Ukkusuri, Satish V. email: sukkusur@purdue.edu organization: Lyles School of Civil Engineering, Purdue University
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/33093497$$D View this record in MEDLINE/PubMed
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Snippet	While large scale mobility data has become a popular tool to monitor the mobility patterns during the COVID-19 pandemic, the impacts of non-compulsory measures... Abstract While large scale mobility data has become a popular tool to monitor the mobility patterns during the COVID-19 pandemic, the impacts of non-compulsory...
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SubjectTerms	639/166 692/699 704/844/1759 Behavior Betacoronavirus - isolation & purification Cell Phone Use - statistics & numerical data Coronavirus Infections - epidemiology Coronavirus Infections - pathology Coronavirus Infections - virology Coronaviruses COVID-19 Humanities and Social Sciences Humans Mobility Movement - physiology multidisciplinary Pandemics Pneumonia, Viral - epidemiology Pneumonia, Viral - pathology Pneumonia, Viral - virology SARS-CoV-2 Science Science (multidisciplinary) Social behavior Time Factors Tokyo - epidemiology
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Title	Non-compulsory measures sufficiently reduced human mobility in Tokyo during the COVID-19 epidemic
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