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Rapid and near real-time assessments of population displacement using mobile phone data following disasters: The 2015 Nepal Earthquake

Rapid and near real-time assessments of population displacement using mobile phone data following disasters: The 2015 Nepal Earthquake
Rapid and near real-time assessments of population displacement using mobile phone data following disasters: The 2015 Nepal Earthquake
Introduction: Sudden impact disasters often result in the displacement of large numbers of people. These movements can occur prior to events, due to early warning messages, or take place post-event due to damages to shelters and livelihoods as well as a result of long-term reconstruction efforts. Displaced populations are especially vulnerable and often in need of support. However, timely and accurate data on the numbers and destinations of displaced populations are extremely challenging to collect across temporal and spatial scales, especially in the aftermath of disasters. Mobile phone call detail records were shown to be a valid data source for estimates of population movements after the 2010 Haiti earthquake, but their potential to provide near real-time ongoing measurements of population displacements immediately after a natural disaster has not been demonstrated.

Methods: A computational architecture and analytical capacity were rapidly deployed within nine days of the Nepal earthquake of 25th April 2015, to provide spatiotemporally detailed estimates of population displacements from call detail records based on movements of 12 million de-identified mobile phones users.

Results: Analysis shows the evolution of population mobility patterns after the earthquake and the patterns of return to affected areas, at a high level of detail. Particularly notable is the movement of an estimated 390,000 people above normal from the Kathmandu valley after the earthquake, with most people moving to surrounding areas and the highly-populated areas in the central southern area of Nepal.

Discussion: This analysis provides an unprecedented level of information about human movement after a natural disaster, provided within a very short timeframe after the earthquake occurred. The patterns revealed using this method are almost impossible to find through other methods, and are of great interest to humanitarian agencies.
Wilson, Robin
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Erbach-Schoenberg, Elisabeth zu
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Albert, Maximilian
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Power, Daniel
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Tudge, Simon
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Gonzalez, Miguel
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Guthrie, Sam
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Chamberlain, Heather
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Brooks, Chris
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Hughes, Christopher
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Pitonakova, Lenka
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Buckee, Caroline O.
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Lu, Xin
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Wetter, Erik
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Tatem, Andrew
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Bengtsson, Linus
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Wilson, Robin
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Erbach-Schoenberg, Elisabeth zu
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Albert, Maximilian
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Power, Daniel
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Tudge, Simon
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Gonzalez, Miguel
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Guthrie, Sam
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Chamberlain, Heather
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Brooks, Chris
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Hughes, Christopher
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Pitonakova, Lenka
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Buckee, Caroline O.
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Lu, Xin
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Wetter, Erik
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Tatem, Andrew
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Bengtsson, Linus
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Wilson, Robin, Erbach-Schoenberg, Elisabeth zu, Albert, Maximilian, Power, Daniel, Tudge, Simon, Gonzalez, Miguel, Guthrie, Sam, Chamberlain, Heather, Brooks, Chris, Hughes, Christopher, Pitonakova, Lenka, Buckee, Caroline O., Lu, Xin, Wetter, Erik, Tatem, Andrew and Bengtsson, Linus (2016) Rapid and near real-time assessments of population displacement using mobile phone data following disasters: The 2015 Nepal Earthquake. PLoS Currents: Outbreaks. (doi:10.1371/currents.dis.d073fbece328e4c39087bc086d694b5c).

Record type: Article

Abstract

Introduction: Sudden impact disasters often result in the displacement of large numbers of people. These movements can occur prior to events, due to early warning messages, or take place post-event due to damages to shelters and livelihoods as well as a result of long-term reconstruction efforts. Displaced populations are especially vulnerable and often in need of support. However, timely and accurate data on the numbers and destinations of displaced populations are extremely challenging to collect across temporal and spatial scales, especially in the aftermath of disasters. Mobile phone call detail records were shown to be a valid data source for estimates of population movements after the 2010 Haiti earthquake, but their potential to provide near real-time ongoing measurements of population displacements immediately after a natural disaster has not been demonstrated.

Methods: A computational architecture and analytical capacity were rapidly deployed within nine days of the Nepal earthquake of 25th April 2015, to provide spatiotemporally detailed estimates of population displacements from call detail records based on movements of 12 million de-identified mobile phones users.

Results: Analysis shows the evolution of population mobility patterns after the earthquake and the patterns of return to affected areas, at a high level of detail. Particularly notable is the movement of an estimated 390,000 people above normal from the Kathmandu valley after the earthquake, with most people moving to surrounding areas and the highly-populated areas in the central southern area of Nepal.

Discussion: This analysis provides an unprecedented level of information about human movement after a natural disaster, provided within a very short timeframe after the earthquake occurred. The patterns revealed using this method are almost impossible to find through other methods, and are of great interest to humanitarian agencies.

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More information

Accepted/In Press date: 23 February 2016
Published date: 24 February 2016

Identifiers

Local EPrints ID: 449870
URI: http://eprints.soton.ac.uk/id/eprint/449870
PURE UUID: 60c5ee02-335d-4597-b261-b114d0eb46a2
ORCID for Heather Chamberlain: ORCID iD orcid.org/0000-0003-0828-6974
ORCID for Andrew Tatem: ORCID iD orcid.org/0000-0002-7270-941X

Catalogue record

Date deposited: 23 Jun 2021 16:31
Last modified: 23 Sep 2021 03:34

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Contributors

Author: Robin Wilson
Author: Elisabeth zu Erbach-Schoenberg
Author: Maximilian Albert
Author: Daniel Power
Author: Simon Tudge
Author: Miguel Gonzalez
Author: Sam Guthrie
Author: Chris Brooks
Author: Christopher Hughes
Author: Lenka Pitonakova
Author: Caroline O. Buckee
Author: Xin Lu
Author: Erik Wetter
Author: Andrew Tatem ORCID iD
Author: Linus Bengtsson

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