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The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology
The ongoing coronavirus disease 2019 (COVID-19) pandemic has heightened discussion of the use of mobile phone data in outbreak response. Mobile phone data have been proposed to monitor effectiveness of non-pharmaceutical interventions, to assess potential drivers of spatiotemporal spread, and to sup...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7528106/ https://www.ncbi.nlm.nih.gov/pubmed/32999287 http://dx.doi.org/10.1038/s41467-020-18190-5 |
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author | Grantz, Kyra H. Meredith, Hannah R. Cummings, Derek A. T. Metcalf, C. Jessica E. Grenfell, Bryan T. Giles, John R. Mehta, Shruti Solomon, Sunil Labrique, Alain Kishore, Nishant Buckee, Caroline O. Wesolowski, Amy |
author_facet | Grantz, Kyra H. Meredith, Hannah R. Cummings, Derek A. T. Metcalf, C. Jessica E. Grenfell, Bryan T. Giles, John R. Mehta, Shruti Solomon, Sunil Labrique, Alain Kishore, Nishant Buckee, Caroline O. Wesolowski, Amy |
author_sort | Grantz, Kyra H. |
collection | PubMed |
description | The ongoing coronavirus disease 2019 (COVID-19) pandemic has heightened discussion of the use of mobile phone data in outbreak response. Mobile phone data have been proposed to monitor effectiveness of non-pharmaceutical interventions, to assess potential drivers of spatiotemporal spread, and to support contact tracing efforts. While these data may be an important part of COVID-19 response, their use must be considered alongside a careful understanding of the behaviors and populations they capture. Here, we review the different applications for mobile phone data in guiding and evaluating COVID-19 response, the relevance of these applications for infectious disease transmission and control, and potential sources and implications of selection bias in mobile phone data. We also discuss best practices and potential pitfalls for directly integrating the collection, analysis, and interpretation of these data into public health decision making. |
format | Online Article Text |
id | pubmed-7528106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75281062020-10-19 The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology Grantz, Kyra H. Meredith, Hannah R. Cummings, Derek A. T. Metcalf, C. Jessica E. Grenfell, Bryan T. Giles, John R. Mehta, Shruti Solomon, Sunil Labrique, Alain Kishore, Nishant Buckee, Caroline O. Wesolowski, Amy Nat Commun Perspective The ongoing coronavirus disease 2019 (COVID-19) pandemic has heightened discussion of the use of mobile phone data in outbreak response. Mobile phone data have been proposed to monitor effectiveness of non-pharmaceutical interventions, to assess potential drivers of spatiotemporal spread, and to support contact tracing efforts. While these data may be an important part of COVID-19 response, their use must be considered alongside a careful understanding of the behaviors and populations they capture. Here, we review the different applications for mobile phone data in guiding and evaluating COVID-19 response, the relevance of these applications for infectious disease transmission and control, and potential sources and implications of selection bias in mobile phone data. We also discuss best practices and potential pitfalls for directly integrating the collection, analysis, and interpretation of these data into public health decision making. Nature Publishing Group UK 2020-09-30 /pmc/articles/PMC7528106/ /pubmed/32999287 http://dx.doi.org/10.1038/s41467-020-18190-5 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Perspective Grantz, Kyra H. Meredith, Hannah R. Cummings, Derek A. T. Metcalf, C. Jessica E. Grenfell, Bryan T. Giles, John R. Mehta, Shruti Solomon, Sunil Labrique, Alain Kishore, Nishant Buckee, Caroline O. Wesolowski, Amy The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology |
title | The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology |
title_full | The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology |
title_fullStr | The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology |
title_full_unstemmed | The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology |
title_short | The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology |
title_sort | use of mobile phone data to inform analysis of covid-19 pandemic epidemiology |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7528106/ https://www.ncbi.nlm.nih.gov/pubmed/32999287 http://dx.doi.org/10.1038/s41467-020-18190-5 |
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