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Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones

Human travel impacts the spread of infectious diseases across spatial and temporal scales, with broad implications for the biological and social sciences. Individual data on travel patterns have been difficult to obtain, particularly in low-income countries. Travel survey data provide detailed demog...

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Autores principales: Wesolowski, Amy, Stresman, Gillian, Eagle, Nathan, Stevenson, Jennifer, Owaga, Chrispin, Marube, Elizabeth, Bousema, Teun, Drakeley, Christopher, Cox, Jonathan, Buckee, Caroline O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4894426/
https://www.ncbi.nlm.nih.gov/pubmed/25022440
http://dx.doi.org/10.1038/srep05678
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author Wesolowski, Amy
Stresman, Gillian
Eagle, Nathan
Stevenson, Jennifer
Owaga, Chrispin
Marube, Elizabeth
Bousema, Teun
Drakeley, Christopher
Cox, Jonathan
Buckee, Caroline O.
author_facet Wesolowski, Amy
Stresman, Gillian
Eagle, Nathan
Stevenson, Jennifer
Owaga, Chrispin
Marube, Elizabeth
Bousema, Teun
Drakeley, Christopher
Cox, Jonathan
Buckee, Caroline O.
author_sort Wesolowski, Amy
collection PubMed
description Human travel impacts the spread of infectious diseases across spatial and temporal scales, with broad implications for the biological and social sciences. Individual data on travel patterns have been difficult to obtain, particularly in low-income countries. Travel survey data provide detailed demographic information, but sample sizes are often small and travel histories are hard to validate. Mobile phone records can provide vast quantities of spatio-temporal travel data but vary in spatial resolution and explicitly do not include individual information in order to protect the privacy of subscribers. Here we compare and contrast both sources of data over the same time period in a rural area of Kenya. Although both data sets are able to quantify broad travel patterns and distinguish regional differences in travel, each provides different insights that can be combined to form a more detailed picture of travel in low-income settings to understand the spread of infectious diseases.
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spelling pubmed-48944262016-06-10 Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones Wesolowski, Amy Stresman, Gillian Eagle, Nathan Stevenson, Jennifer Owaga, Chrispin Marube, Elizabeth Bousema, Teun Drakeley, Christopher Cox, Jonathan Buckee, Caroline O. Sci Rep Article Human travel impacts the spread of infectious diseases across spatial and temporal scales, with broad implications for the biological and social sciences. Individual data on travel patterns have been difficult to obtain, particularly in low-income countries. Travel survey data provide detailed demographic information, but sample sizes are often small and travel histories are hard to validate. Mobile phone records can provide vast quantities of spatio-temporal travel data but vary in spatial resolution and explicitly do not include individual information in order to protect the privacy of subscribers. Here we compare and contrast both sources of data over the same time period in a rural area of Kenya. Although both data sets are able to quantify broad travel patterns and distinguish regional differences in travel, each provides different insights that can be combined to form a more detailed picture of travel in low-income settings to understand the spread of infectious diseases. Nature Publishing Group 2014-07-14 /pmc/articles/PMC4894426/ /pubmed/25022440 http://dx.doi.org/10.1038/srep05678 Text en Copyright © 2014, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/
spellingShingle Article
Wesolowski, Amy
Stresman, Gillian
Eagle, Nathan
Stevenson, Jennifer
Owaga, Chrispin
Marube, Elizabeth
Bousema, Teun
Drakeley, Christopher
Cox, Jonathan
Buckee, Caroline O.
Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones
title Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones
title_full Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones
title_fullStr Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones
title_full_unstemmed Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones
title_short Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones
title_sort quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4894426/
https://www.ncbi.nlm.nih.gov/pubmed/25022440
http://dx.doi.org/10.1038/srep05678
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