Evidence map›Paper›PMID 32213647›Full record

ArticleScience (New York, N.Y.)2020

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

Moritz U G Kraemer, Chia-Hung Yang, Bernardo Gutierrez, Chieh-Hsi Wu, Brennan Klein, David M Pigott, Open COVID-19 Data Working Group, Louis du Plessis, Nuno R Faria, Ruoran Li and 8 more

Abstract read
In one paragraph

Article in Science (New York, N.Y.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,249 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,249citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1,249 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Effectiveness of social distancing measures and lockdowns for reducing transmission of COVID-19 in non-healthcare, community-based settings.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2023
    Pooled it
  2. Influence of non-pharmaceutical COVID-19 interventions on speed-related and alcohol-related traffic injuries in five cities of the province of Québec, Canada.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2026
    Article
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  17. HIV Transmission Dynamics in Greater Mexico City are Shaped by Dense Spatial Mixing.medRxiv : the preprint server for health sciences · 2026
    Article
  18. Review
  19. Article
  20. Article

1,189 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors.

Moritz U G KraemerDepartment of Zoology, University of Oxford, Oxford, UK. s.scarpino@northeastern.edu oliver.pybus@zoo.ox.ac.uk moritz.kraemer@zoo.ox.ac.uk.ORCID 0000-0001-8838-7147
Chia-Hung YangNetwork Science Institute, Northeastern University, Boston, MA, USA.
Bernardo GutierrezDepartment of Zoology, University of Oxford, Oxford, UK.ORCID 0000-0002-9220-2739
Chieh-Hsi WuMathematical Sciences, University of Southampton, Southampton, UK.ORCID 0000-0001-9386-725X
Brennan KleinNetwork Science Institute, Northeastern University, Boston, MA, USA.ORCID 0000-0001-8326-5044
David M PigottInstitute for Health Metrics and Evaluation, Department of Health Metrics, University of Washington, Seattle, WA, USA.ORCID 0000-0002-6731-4034
Open COVID-19 Data Working Group
Louis du PlessisDepartment of Zoology, University of Oxford, Oxford, UK.ORCID 0000-0003-0352-6289
Nuno R FariaDepartment of Zoology, University of Oxford, Oxford, UK.ORCID 0000-0001-8839-2798
Ruoran LiHarvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0001-7575-2758
William P HanageHarvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0002-6319-7336
John S BrownsteinHarvard Medical School, Harvard University, Boston, MA, USA.
Maylis LayanMathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.
Alessandro VespignaniNetwork Science Institute, Northeastern University, Boston, MA, USA.ORCID 0000-0003-3419-4205
Huaiyu TianState Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China.
Christopher DyeDepartment of Zoology, University of Oxford, Oxford, UK.ORCID 0000-0002-2957-1793
Oliver G PybusDepartment of Zoology, University of Oxford, Oxford, UK. s.scarpino@northeastern.edu oliver.pybus@zoo.ox.ac.uk moritz.kraemer@zoo.ox.ac.uk.ORCID 0000-0002-8797-2667
Samuel V ScarpinoNetwork Science Institute, Northeastern University, Boston, MA, USA. s.scarpino@northeastern.edu oliver.pybus@zoo.ox.ac.uk moritz.kraemer@zoo.ox.ac.uk.ORCID 0000-0001-5716-2770

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI HANAGE, WILLIAM · 2009 to 2018
$26.4M
Epidemiology of Infectious Diseases and BiodefenseT32AI007535 · NIAID · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI GRAD, YONATAN H, MURRAY, MEGAN B · 1998 to 2025
$4.8M
Deep sequencing of pathogens to precisely define transmission networks using rare variantsR01AI128344 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI HANAGE, WILLIAM · 2017 to 2021
$3.4M
Medical Research Council MC_PC_19012Medical Research Council MR/R015600/1Medical Research Council MR/S019510/1NIAID NIH HHS R01 AI128344NIAID NIH HHS T32 AI007535NIGMS NIH HHS U54 GM088558
6 · The paper itself

Abstract

The ongoing coronavirus disease 2019 (COVID-19) outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions were undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We used real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. After the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside of Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.

Indexed as

Age DistributionBetacoronavirusChinaCoronavirus InfectionsCOVID-19Epidemiological MonitoringFemaleHumansLinear ModelsMalePandemicsPneumonia, ViralSARS-CoV-2Sex DistributionSpatial AnalysisTravel

Identifiers

PMID32213647
PMCPMC7146642

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.