The effect of human mobility and control measures on the COVID-19 epidemic in China
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- Moritz U. G. Kraemer
- Department of Zoology, University of Oxford, Oxford, UK.
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- Chia-Hung Yang
- Network Science Institute, Northeastern University, Boston, MA, USA.
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- Bernardo Gutierrez
- Department of Zoology, University of Oxford, Oxford, UK.
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- Chieh-Hsi Wu
- Mathematical Sciences, University of Southampton, Southampton, UK.
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- Brennan Klein
- Network Science Institute, Northeastern University, Boston, MA, USA.
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- David M. Pigott
- Institute for Health Metrics and Evaluation, Department of Health Metrics, University of Washington, Seattle, WA, USA.
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- Louis du Plessis
- Department of Zoology, University of Oxford, Oxford, UK.
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- Nuno R. Faria
- Department of Zoology, University of Oxford, Oxford, UK.
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- Ruoran Li
- Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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- William P. Hanage
- Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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- John S. Brownstein
- Harvard Medical School, Harvard University, Boston, MA, USA.
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- Maylis Layan
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.
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- Alessandro Vespignani
- Network Science Institute, Northeastern University, Boston, MA, USA.
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- Huaiyu Tian
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China.
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- Christopher Dye
- Department of Zoology, University of Oxford, Oxford, UK.
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- Oliver G. Pybus
- Department of Zoology, University of Oxford, Oxford, UK.
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- Samuel V. Scarpino
- Network Science Institute, Northeastern University, Boston, MA, USA.
説明
<jats:title>Tracing infection from mobility data</jats:title> <jats:p> What sort of measures are required to contain the spread of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19)? The rich data from the Open COVID-19 Data Working Group include the dates when people first reported symptoms, not just a positive test date. Using these data and real-time travel data from the internet services company Baidu, Kraemer <jats:italic>et al.</jats:italic> found that mobility statistics offered a precise record of the spread of SARS-CoV-2 among the cities of China at the start of 2020. The frequency of introductions from Wuhan were predictive of the size of the epidemic sparked in other provinces. However, once the virus had escaped Wuhan, strict local control measures such as social isolation and hygiene, rather than long-distance travel restrictions, played the largest part in controlling SARS-CoV-2 spread. </jats:p> <jats:p> <jats:italic>Science</jats:italic> , this issue p. <jats:related-article xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="doi" issue="6490" page="493" related-article-type="in-this-issue" vol="368" xlink:href="10.1126/science.abb4218">493</jats:related-article> </jats:p>
収録刊行物
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- Science
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Science 368 (6490), 493-497, 2020-05
American Association for the Advancement of Science (AAAS)
