Mapping global variation in human mobility.


Journal

Nature human behaviour
ISSN: 2397-3374
Titre abrégé: Nat Hum Behav
Pays: England
ID NLM: 101697750

Informations de publication

Date de publication:
08 2020
Historique:
received: 13 04 2019
accepted: 30 03 2020
pubmed: 20 5 2020
medline: 18 11 2020
entrez: 20 5 2020
Statut: ppublish

Résumé

The geographic variation of human movement is largely unknown, mainly due to a lack of accurate and scalable data. Here we describe global human mobility patterns, aggregated from over 300 million smartphone users. The data cover nearly all countries and 65% of Earth's populated surface, including cross-border movements and international migration. This scale and coverage enable us to develop a globally comprehensive human movement typology. We quantify how human movement patterns vary across sociodemographic and environmental contexts and present international movement patterns across national borders. Fitting statistical models, we validate our data and find that human movement laws apply at 10 times shorter distances and movement declines 40% more rapidly in low-income settings. These results and data are made available to further understanding of the role of human movement in response to rapid demographic, economic and environmental changes.

Identifiants

pubmed: 32424257
doi: 10.1038/s41562-020-0875-0
pii: 10.1038/s41562-020-0875-0
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

800-810

Subventions

Organisme : NICHD NIH HHS
ID : T32 HD040128
Pays : United States
Organisme : NLM NIH HHS
ID : R01 LM010812
Pays : United States
Organisme : NLM NIH HHS
ID : R01 LM011965
Pays : United States

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Auteurs

Moritz U G Kraemer (MUG)

Harvard Medical School, Harvard University, Boston, MA, USA. moritz.kraemer@zoo.ox.ac.uk.
Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA. moritz.kraemer@zoo.ox.ac.uk.
Department of Zoology, University of Oxford, Oxford, UK. moritz.kraemer@zoo.ox.ac.uk.

Adam Sadilek (A)

Google Inc., Mountain View, CA, USA.

Qian Zhang (Q)

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

Nahema A Marchal (NA)

Oxford Internet Institute, University of Oxford, Oxford, UK.

Gaurav Tuli (G)

Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA.

Emily L Cohn (EL)

Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA.

Yulin Hswen (Y)

Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA.
Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.

T Alex Perkins (TA)

Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA.

David L Smith (DL)

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

Robert C Reiner (RC)

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. bcreiner@uw.edu.
Department of Health Metrics Sciences, University of Washington, Seattle, WA, USA. bcreiner@uw.edu.

John S Brownstein (JS)

Harvard Medical School, Harvard University, Boston, MA, USA. john.brownstein@childrens.harvard.edu.
Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, USA. john.brownstein@childrens.harvard.edu.

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