Characterizing human mobility patterns in rural settings of sub-Saharan Africa

Human mobility is a core component of human behavior and its quantification is critical for understanding its impact on infectious disease transmission, traffic forecasting, access to resources and care, intervention strategies, and migratory flows. When mobility data are limited, spatial interactio...

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Autores principales:	Hannah R Meredith, John R Giles, Javier Perez-Saez, Théophile Mande, Andrea Rinaldo, Simon Mutembo, Elliot N Kabalo, Kabondo Makungo, Caroline O Buckee, Andrew J Tatem, C Jessica E Metcalf, Amy Wesolowski
Formato:	article
Lenguaje:	EN
Publicado:	eLife Sciences Publications Ltd 2021
Materias:	Human mobility spatial models mobile phone data gravity model low and middle income countries Medicine R Science Q Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/73cfd5407c0746ffbf9bb91ff095993f
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id	oai:doaj.org-article:73cfd5407c0746ffbf9bb91ff095993f
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spelling	oai:doaj.org-article:73cfd5407c0746ffbf9bb91ff095993f2021-11-25T10:27:18ZCharacterizing human mobility patterns in rural settings of sub-Saharan Africa10.7554/eLife.684412050-084Xe68441https://doaj.org/article/73cfd5407c0746ffbf9bb91ff095993f2021-09-01T00:00:00Zhttps://elifesciences.org/articles/68441https://doaj.org/toc/2050-084XHuman mobility is a core component of human behavior and its quantification is critical for understanding its impact on infectious disease transmission, traffic forecasting, access to resources and care, intervention strategies, and migratory flows. When mobility data are limited, spatial interaction models have been widely used to estimate human travel, but have not been extensively validated in low- and middle-income settings. Geographic, sociodemographic, and infrastructure differences may impact the ability for models to capture these patterns, particularly in rural settings. Here, we analyzed mobility patterns inferred from mobile phone data in four Sub-Saharan African countries to investigate the ability for variants on gravity and radiation models to estimate travel. Adjusting the gravity model such that parameters were fit to different trip types, including travel between more or less populated areas and/or different regions, improved model fit in all four countries. This suggests that alternative models may be more useful in these settings and better able to capture the range of mobility patterns observed.Hannah R MeredithJohn R GilesJavier Perez-SaezThéophile MandeAndrea RinaldoSimon MutemboElliot N KabaloKabondo MakungoCaroline O BuckeeAndrew J TatemC Jessica E MetcalfAmy WesolowskieLife Sciences Publications LtdarticleHuman mobilityspatial modelsmobile phone datagravity modellow and middle income countriesMedicineRScienceQBiology (General)QH301-705.5ENeLife, Vol 10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Human mobility spatial models mobile phone data gravity model low and middle income countries Medicine R Science Q Biology (General) QH301-705.5
spellingShingle	Human mobility spatial models mobile phone data gravity model low and middle income countries Medicine R Science Q Biology (General) QH301-705.5 Hannah R Meredith John R Giles Javier Perez-Saez Théophile Mande Andrea Rinaldo Simon Mutembo Elliot N Kabalo Kabondo Makungo Caroline O Buckee Andrew J Tatem C Jessica E Metcalf Amy Wesolowski Characterizing human mobility patterns in rural settings of sub-Saharan Africa
description	Human mobility is a core component of human behavior and its quantification is critical for understanding its impact on infectious disease transmission, traffic forecasting, access to resources and care, intervention strategies, and migratory flows. When mobility data are limited, spatial interaction models have been widely used to estimate human travel, but have not been extensively validated in low- and middle-income settings. Geographic, sociodemographic, and infrastructure differences may impact the ability for models to capture these patterns, particularly in rural settings. Here, we analyzed mobility patterns inferred from mobile phone data in four Sub-Saharan African countries to investigate the ability for variants on gravity and radiation models to estimate travel. Adjusting the gravity model such that parameters were fit to different trip types, including travel between more or less populated areas and/or different regions, improved model fit in all four countries. This suggests that alternative models may be more useful in these settings and better able to capture the range of mobility patterns observed.
format	article
author	Hannah R Meredith John R Giles Javier Perez-Saez Théophile Mande Andrea Rinaldo Simon Mutembo Elliot N Kabalo Kabondo Makungo Caroline O Buckee Andrew J Tatem C Jessica E Metcalf Amy Wesolowski
author_facet	Hannah R Meredith John R Giles Javier Perez-Saez Théophile Mande Andrea Rinaldo Simon Mutembo Elliot N Kabalo Kabondo Makungo Caroline O Buckee Andrew J Tatem C Jessica E Metcalf Amy Wesolowski
author_sort	Hannah R Meredith
title	Characterizing human mobility patterns in rural settings of sub-Saharan Africa
title_short	Characterizing human mobility patterns in rural settings of sub-Saharan Africa
title_full	Characterizing human mobility patterns in rural settings of sub-Saharan Africa
title_fullStr	Characterizing human mobility patterns in rural settings of sub-Saharan Africa
title_full_unstemmed	Characterizing human mobility patterns in rural settings of sub-Saharan Africa
title_sort	characterizing human mobility patterns in rural settings of sub-saharan africa
publisher	eLife Sciences Publications Ltd
publishDate	2021
url	https://doaj.org/article/73cfd5407c0746ffbf9bb91ff095993f
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Characterizing human mobility patterns in rural settings of sub-Saharan Africa

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