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The use of census migration data to approximate human movement patterns across temporal scales

The use of census migration data to approximate human movement patterns across temporal scales
The use of census migration data to approximate human movement patterns across temporal scales
Human movement plays a key role in economies and development, the delivery of services, and the spread of infectious diseases. However, it remains poorly quantified partly because reliable data are often lacking, particularly for low-income countries. The most widely available are migration data from human population censuses, which provide valuable information on relatively long timescale relocations across countries, but do not capture the shorter-scale patterns, trips less than a year, that make up the bulk of human movement. Census-derived migration data may provide valuable proxies for shorter-term movements however, as substantial migration between regions can be indicative of well connected places exhibiting high levels of movement at finer time scales, but this has never been examined in detail. Here, an extensive mobile phone usage data set for Kenya was processed to extract movements between counties in 2009 on weekly, monthly, and annual time scales and compared to data on change in residence from the national census conducted during the same time period. We find that the relative ordering across Kenyan counties for incoming, outgoing and between-county movements shows strong correlations. Moreover, the distributions of trip durations from both sources of data are similar, and a spatial interaction model fit to the data reveals the relationships of different parameters over a range of movement time scales. Significant relationships between census migration data and fine temporal scale movement patterns exist, and results suggest that census data can be used to approximate certain features of movement patterns across multiple temporal scales, extending the utility of census-derived migration data.
1932-6203
e52971
Wesolowski, Amy
343b0df8-5a2f-46e2-9f1c-001d4adf7fb1
Buckee, Caroline O.
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Pindolia, Deepa K.
f207589b-cc5b-4daa-8d17-ff674d73c046
Eagle, Nathan
7936c351-0cae-47be-b0c1-e3f0f331d885
Smith, David L.
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Garcia, Andres J.
66af41c0-7fd4-4f11-b5bc-5333b4c04824
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Wesolowski, Amy
343b0df8-5a2f-46e2-9f1c-001d4adf7fb1
Buckee, Caroline O.
f4bc891c-4f42-46a6-822d-03fc1f9cd55b
Pindolia, Deepa K.
f207589b-cc5b-4daa-8d17-ff674d73c046
Eagle, Nathan
7936c351-0cae-47be-b0c1-e3f0f331d885
Smith, David L.
5c918948-ded2-42d8-82c1-a746a4bc3b6e
Garcia, Andres J.
66af41c0-7fd4-4f11-b5bc-5333b4c04824
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e

Wesolowski, Amy, Buckee, Caroline O., Pindolia, Deepa K., Eagle, Nathan, Smith, David L., Garcia, Andres J. and Tatem, Andrew J. (2013) The use of census migration data to approximate human movement patterns across temporal scales. PLoS ONE, 8 (1), e52971. (doi:10.1371/journal.pone.0052971). (PMID:23326367)

Record type: Article

Abstract

Human movement plays a key role in economies and development, the delivery of services, and the spread of infectious diseases. However, it remains poorly quantified partly because reliable data are often lacking, particularly for low-income countries. The most widely available are migration data from human population censuses, which provide valuable information on relatively long timescale relocations across countries, but do not capture the shorter-scale patterns, trips less than a year, that make up the bulk of human movement. Census-derived migration data may provide valuable proxies for shorter-term movements however, as substantial migration between regions can be indicative of well connected places exhibiting high levels of movement at finer time scales, but this has never been examined in detail. Here, an extensive mobile phone usage data set for Kenya was processed to extract movements between counties in 2009 on weekly, monthly, and annual time scales and compared to data on change in residence from the national census conducted during the same time period. We find that the relative ordering across Kenyan counties for incoming, outgoing and between-county movements shows strong correlations. Moreover, the distributions of trip durations from both sources of data are similar, and a spatial interaction model fit to the data reveals the relationships of different parameters over a range of movement time scales. Significant relationships between census migration data and fine temporal scale movement patterns exist, and results suggest that census data can be used to approximate certain features of movement patterns across multiple temporal scales, extending the utility of census-derived migration data.

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Published date: January 2013
Organisations: Global Env Change & Earth Observation, WorldPop, Geography & Environment, PHEW – S (Spatial analysis and modelling), Population, Health & Wellbeing (PHeW)

Identifiers

Local EPrints ID: 347374
URI: https://eprints.soton.ac.uk/id/eprint/347374
ISSN: 1932-6203
PURE UUID: 1d4a2fa7-7d3f-4a65-ab64-ba5b82656af5
ORCID for Andrew J. Tatem: ORCID iD orcid.org/0000-0002-7270-941X

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Date deposited: 21 Jan 2013 16:27
Last modified: 03 Dec 2019 01:38

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Contributors

Author: Amy Wesolowski
Author: Caroline O. Buckee
Author: Deepa K. Pindolia
Author: Nathan Eagle
Author: David L. Smith
Author: Andres J. Garcia
Author: Andrew J. Tatem ORCID iD

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