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Publication . Article . Preprint . 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; Louis du Plessis; +10 Authors
Open Access

doi: 10.1101/2020.03.02.20026708 , 10.1126/science.abb4218 , 10.17863/cam.52824

pmid: 32511452 , 32213647

pmc: PMC7146642 , PMC7239080

Published: 06 Mar 2020
Publisher: Cold Spring Harbor Laboratory
Abstract

The ongoing COVID-19 outbreak has expanded rapidly throughout China. Major behavioral, clinical, and state interventions are underway currently 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, have affected COVID-19 spread in China. We use real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation on transmission in cities across China and ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was well explained by human mobility data. Following the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases are still indicative of local chains of transmission outside Wuhan. This study shows that the drastic control measures implemented in China have substantially mitigated the spread of COVID-19.

One sentence summary: The spread of COVID-19 in China was driven by human mobility early on and mitigated substantially by drastic control measures implemented since the end of January.

Subjects by Vocabulary

Microsoft Academic Graph classification: Socioeconomics China Geography Transmission (mechanics) law.invention law Psychological intervention Outbreak Coronavirus disease 2019 (COVID-19) Demographics Control (management) Environmental health 2019-20 coronavirus outbreak Epidemiological Monitoring

Subjects

Multidisciplinary, Age Distribution, Betacoronavirus, COVID-19, China, Coronavirus Infections, Epidemiological Monitoring, Humans, Linear Models, Pandemics, Pneumonia, Viral, SARS-CoV-2, Sex Distribution, Spatial Analysis, Travel, Article, [SDV]Life Sciences [q-bio], [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Research Article, Research Articles, R-Articles, Ecology, Epidemiology, Coronavirus, Open COVID-19 Data Working Group, Open COVID-19 Data Working Group, Humans, Pneumonia, Viral, Coronavirus Infections, Linear Models, Age Distribution, Sex Distribution, Travel, China, Pandemics, Epidemiological Monitoring, Spatial Analysis, Betacoronavirus, COVID-19, SARS-CoV-2, [SDV] Life Sciences [q-bio], [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology

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Funded by
NIH| MIDAS Center for Communicable Disease Dynamics
Project
MIDAS Center for Communicable Disease Dynamics
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1U54GM088558-01
  • Funding stream: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
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