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Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan
ABSTRACT: BACKGROUND: As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or li...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7838857/ https://www.ncbi.nlm.nih.gov/pubmed/33504339 http://dx.doi.org/10.1186/s12889-021-10260-7 |
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author | Chang, Meng-Chun Kahn, Rebecca Li, Yu-An Lee, Cheng-Sheng Buckee, Caroline O. Chang, Hsiao-Han |
author_facet | Chang, Meng-Chun Kahn, Rebecca Li, Yu-An Lee, Cheng-Sheng Buckee, Caroline O. Chang, Hsiao-Han |
author_sort | Chang, Meng-Chun |
collection | PubMed |
description | ABSTRACT: BACKGROUND: As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases. METHODS: In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan. RESULTS: We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas that may serve as sources of importation during an outbreak. We showed that the risk of an outbreak in Taiwan is enhanced if initial infections occur around holidays. Intracity travel reductions have a higher impact on the risk of an outbreak than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. CONCLUSIONS: To prepare for the potential spread within Taiwan, we utilized Facebook’s aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. We developed an interactive application that allows users to vary inputs and assumptions and shows the spatial spread of the disease and the impact of intercity and intracity travel reduction under different initial conditions. Our results can be used readily if local transmission occurs in Taiwan after relaxation of border control, providing important insights into future disease surveillance and policies for travel restrictions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-10260-7. |
format | Online Article Text |
id | pubmed-7838857 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-78388572021-01-27 Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan Chang, Meng-Chun Kahn, Rebecca Li, Yu-An Lee, Cheng-Sheng Buckee, Caroline O. Chang, Hsiao-Han BMC Public Health Research Article ABSTRACT: BACKGROUND: As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases. METHODS: In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan. RESULTS: We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas that may serve as sources of importation during an outbreak. We showed that the risk of an outbreak in Taiwan is enhanced if initial infections occur around holidays. Intracity travel reductions have a higher impact on the risk of an outbreak than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. CONCLUSIONS: To prepare for the potential spread within Taiwan, we utilized Facebook’s aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. We developed an interactive application that allows users to vary inputs and assumptions and shows the spatial spread of the disease and the impact of intercity and intracity travel reduction under different initial conditions. Our results can be used readily if local transmission occurs in Taiwan after relaxation of border control, providing important insights into future disease surveillance and policies for travel restrictions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-10260-7. BioMed Central 2021-01-27 /pmc/articles/PMC7838857/ /pubmed/33504339 http://dx.doi.org/10.1186/s12889-021-10260-7 Text en © The Author(s) 2021 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Chang, Meng-Chun Kahn, Rebecca Li, Yu-An Lee, Cheng-Sheng Buckee, Caroline O. Chang, Hsiao-Han Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan |
title | Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan |
title_full | Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan |
title_fullStr | Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan |
title_full_unstemmed | Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan |
title_short | Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan |
title_sort | variation in human mobility and its impact on the risk of future covid-19 outbreaks in taiwan |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7838857/ https://www.ncbi.nlm.nih.gov/pubmed/33504339 http://dx.doi.org/10.1186/s12889-021-10260-7 |
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