The effect of human mobility and control measures on the COVID-19 epidemic in China

Author:

Kraemer Moritz U. G.123ORCID,Yang Chia-Hung4,Gutierrez Bernardo15ORCID,Wu Chieh-Hsi6ORCID,Klein Brennan4ORCID,Pigott David M.7ORCID,du Plessis Louis1ORCID,Faria Nuno R.1ORCID,Li Ruoran8ORCID,Hanage William P.8ORCID,Brownstein John S.23,Layan Maylis910,Vespignani Alessandro411ORCID,Tian Huaiyu12,Dye Christopher1ORCID,Pybus Oliver G.113ORCID,Scarpino Samuel V.4ORCID,

Affiliation:

1. Department of Zoology, University of Oxford, Oxford, UK.

2. Harvard Medical School, Harvard University, Boston, MA, USA.

3. Boston Children’s Hospital, Boston, MA, USA.

4. Network Science Institute, Northeastern University, Boston, MA, USA.

5. School of Biological and Environmental Sciences, Universidad San Francisco de Quito USFQ, Quito, Ecuador.

6. Mathematical Sciences, University of Southampton, Southampton, UK.

7. Institute for Health Metrics and Evaluation, Department of Health Metrics, University of Washington, Seattle, WA, USA.

8. Harvard T.H. Chan School of Public Health, Boston, MA, USA.

9. Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.

10. Sorbonne Université, Paris, France.

11. ISI Foundation, Turin, Italy.

12. State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China.

13. Department of Pathobiology and Population Sciences, The Royal Veterinary College, London, UK.

Abstract

Tracing infection from mobility data 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 et al. 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. Science , this issue p. 493

Funder

Oxford Martin School, University of Oxford

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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