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A systematic review of using population-level human mobility data to understand SARS-CoV-2 transmission

A systematic review of using population-level human mobility data to understand SARS-CoV-2 transmission
A systematic review of using population-level human mobility data to understand SARS-CoV-2 transmission

The emergence of SARS-CoV-2 into a highly susceptible global population was primarily driven by human mobility-induced introduction events. Especially in the early stages, understanding mobility was vital to mitigating the pandemic prior to widespread vaccine availability. We conducted a systematic review of studies published from January 1, 2020, to May 9, 2021, that used population-level human mobility data to understand SARS-CoV-2 transmission. Of the 5505 papers with abstracts screened, 232 were included in the analysis. These papers focused on a range of specific questions but were dominated by analyses focusing on the USA and China. The majority included mobile phone data, followed by Google Community Mobility Reports, and few included any adjustments to account for potential biases in population sampling processes. There was no clear relationship between methods used to integrate mobility and SARS-CoV-2 data and goals of analysis. When considering papers focused only on the estimation of the effective reproductive number within the US, there was no clear relationship identified between this measure and changes in mobility patterns. Our findings underscore the need for standardized, systematic ways to identify the source of mobility data, select an appropriate approach to using it in analysis, and reporting.

Basic Reproduction Number/statistics & numerical data, COVID-19/transmission, Cell Phone, China/epidemiology, Humans, Pandemics/prevention & control, SARS-CoV-2, Travel/statistics & numerical data, United States/epidemiology
2041-1723
Kostandova, Natalya
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Schluth, Catherine
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Arambepola, Rohan
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Atuhaire, Fatumah
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Bérubé, Sophie
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Chin, Taylor
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Cleary, Eimear
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Cortes-Azuero, Oscar
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García-Carreras, Bernardo
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Grantz, Kyra H.
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Hitchings, Matt D.T.
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Huang, Angkana T.
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Kishore, Nishant
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Lai, Shengjie
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Larsen, Sophie L.
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Loisate, Stacie
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Martinez, Pamela
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Meredith, Hannah R.
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Purbey, Ritika
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Ramiadantsoa, Tanjona
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Read, Jonathan
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Rice, Benjamin L.
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Rosman, Lori
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Ruktanonchai, Nick
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Salje, Henrik
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Schaber, Kathryn L.
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Tatem, Andrew J.
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Wang, Jasmine
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Cummings, Derek A T
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Wesolowski, Amy
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et al.
Kostandova, Natalya
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Schluth, Catherine
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Arambepola, Rohan
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Atuhaire, Fatumah
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Bérubé, Sophie
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Chin, Taylor
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Cleary, Eimear
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Cortes-Azuero, Oscar
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García-Carreras, Bernardo
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Grantz, Kyra H.
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Hitchings, Matt D.T.
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Huang, Angkana T.
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Kishore, Nishant
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Lai, Shengjie
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Larsen, Sophie L.
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Loisate, Stacie
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Martinez, Pamela
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Meredith, Hannah R.
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Purbey, Ritika
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Ramiadantsoa, Tanjona
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Read, Jonathan
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Rice, Benjamin L.
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Rosman, Lori
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Ruktanonchai, Nick
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Salje, Henrik
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Schaber, Kathryn L.
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Tatem, Andrew J.
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Wang, Jasmine
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Cummings, Derek A T
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Wesolowski, Amy
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Kostandova, Natalya, Schluth, Catherine and Arambepola, Rohan , et al. (2024) A systematic review of using population-level human mobility data to understand SARS-CoV-2 transmission. Nature Communications, 15 (1), [10504]. (doi:10.1038/s41467-024-54895-7).

Record type: Article

Abstract

The emergence of SARS-CoV-2 into a highly susceptible global population was primarily driven by human mobility-induced introduction events. Especially in the early stages, understanding mobility was vital to mitigating the pandemic prior to widespread vaccine availability. We conducted a systematic review of studies published from January 1, 2020, to May 9, 2021, that used population-level human mobility data to understand SARS-CoV-2 transmission. Of the 5505 papers with abstracts screened, 232 were included in the analysis. These papers focused on a range of specific questions but were dominated by analyses focusing on the USA and China. The majority included mobile phone data, followed by Google Community Mobility Reports, and few included any adjustments to account for potential biases in population sampling processes. There was no clear relationship between methods used to integrate mobility and SARS-CoV-2 data and goals of analysis. When considering papers focused only on the estimation of the effective reproductive number within the US, there was no clear relationship identified between this measure and changes in mobility patterns. Our findings underscore the need for standardized, systematic ways to identify the source of mobility data, select an appropriate approach to using it in analysis, and reporting.

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s41467-024-54895-7 - Version of Record
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More information

Accepted/In Press date: 25 November 2024
Published date: 3 December 2024
Additional Information: © 2024. The Author(s).
Keywords: Basic Reproduction Number/statistics & numerical data, COVID-19/transmission, Cell Phone, China/epidemiology, Humans, Pandemics/prevention & control, SARS-CoV-2, Travel/statistics & numerical data, United States/epidemiology

Identifiers

Local EPrints ID: 497035
URI: http://eprints.soton.ac.uk/id/eprint/497035
ISSN: 2041-1723
PURE UUID: e538ed9a-c01e-477a-a243-736ce9a928f8
ORCID for Eimear Cleary: ORCID iD orcid.org/0000-0003-2549-8565
ORCID for Shengjie Lai: ORCID iD orcid.org/0000-0001-9781-8148
ORCID for Andrew J. Tatem: ORCID iD orcid.org/0000-0002-7270-941X

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Date deposited: 10 Jan 2025 17:42
Last modified: 22 Aug 2025 02:32

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Contributors

Author: Natalya Kostandova
Author: Catherine Schluth
Author: Rohan Arambepola
Author: Fatumah Atuhaire
Author: Sophie Bérubé
Author: Taylor Chin
Author: Eimear Cleary ORCID iD
Author: Oscar Cortes-Azuero
Author: Bernardo García-Carreras
Author: Kyra H. Grantz
Author: Matt D.T. Hitchings
Author: Angkana T. Huang
Author: Nishant Kishore
Author: Shengjie Lai ORCID iD
Author: Sophie L. Larsen
Author: Stacie Loisate
Author: Pamela Martinez
Author: Hannah R. Meredith
Author: Ritika Purbey
Author: Tanjona Ramiadantsoa
Author: Jonathan Read
Author: Benjamin L. Rice
Author: Lori Rosman
Author: Nick Ruktanonchai
Author: Henrik Salje
Author: Kathryn L. Schaber
Author: Andrew J. Tatem ORCID iD
Author: Jasmine Wang
Author: Derek A T Cummings
Author: Amy Wesolowski
Corporate Author: et al.

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