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A measure to estimate the risk of imported COVID-19 cases and its application for evaluating travel-related control measures

High connectivity between nations facilitates the spread of infectious diseases. We introduce an improved measure to estimate the risk of COVID-19 importation. The measure was applied to identify the effectiveness of travel-related control measures. We estimated the risk of importation, using the pr...

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Autores principales: Kang, Heewon, Min, Kyung-Duk, Jeon, Seonghee, Lee, Ju-Yeun, Cho, Sung-il
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9178220/
https://www.ncbi.nlm.nih.gov/pubmed/35681085
http://dx.doi.org/10.1038/s41598-022-13775-0
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author Kang, Heewon
Min, Kyung-Duk
Jeon, Seonghee
Lee, Ju-Yeun
Cho, Sung-il
author_facet Kang, Heewon
Min, Kyung-Duk
Jeon, Seonghee
Lee, Ju-Yeun
Cho, Sung-il
author_sort Kang, Heewon
collection PubMed
description High connectivity between nations facilitates the spread of infectious diseases. We introduce an improved measure to estimate the risk of COVID-19 importation. The measure was applied to identify the effectiveness of travel-related control measures. We estimated the risk of importation, using the product of air-travel volume and COVID-19 prevalence in the area-of-origin. Travel volumes were acquired through real-time mobile data, and prevalence was calculated considering the time-varying strength of the COVID-19 testing policy. With the measure, the number of expected-imported cases was calculated, and compared with the reported-imported COVID-19 cases before and after post-entry quarantine for all entrants. The expected and reported-imported cases were well fitted (R(2) = 0.8). A maximum of 35 undetected-imported cases was estimated to have entered Seoul, before the first imported COVID-19 case was confirmed. With the travel-related control measures, at most, 48 (73%) imported cases could be isolated from the local community. Our measure predicted trends in imported COVID-19 cases well. The method used to develop the measure can be applied to future emerging infectious diseases. Our results provide a ‘real-world’ evidence that travel-related control measures are effective at curbing further COVID-19 transmission.
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spelling pubmed-91782202022-06-09 A measure to estimate the risk of imported COVID-19 cases and its application for evaluating travel-related control measures Kang, Heewon Min, Kyung-Duk Jeon, Seonghee Lee, Ju-Yeun Cho, Sung-il Sci Rep Article High connectivity between nations facilitates the spread of infectious diseases. We introduce an improved measure to estimate the risk of COVID-19 importation. The measure was applied to identify the effectiveness of travel-related control measures. We estimated the risk of importation, using the product of air-travel volume and COVID-19 prevalence in the area-of-origin. Travel volumes were acquired through real-time mobile data, and prevalence was calculated considering the time-varying strength of the COVID-19 testing policy. With the measure, the number of expected-imported cases was calculated, and compared with the reported-imported COVID-19 cases before and after post-entry quarantine for all entrants. The expected and reported-imported cases were well fitted (R(2) = 0.8). A maximum of 35 undetected-imported cases was estimated to have entered Seoul, before the first imported COVID-19 case was confirmed. With the travel-related control measures, at most, 48 (73%) imported cases could be isolated from the local community. Our measure predicted trends in imported COVID-19 cases well. The method used to develop the measure can be applied to future emerging infectious diseases. Our results provide a ‘real-world’ evidence that travel-related control measures are effective at curbing further COVID-19 transmission. Nature Publishing Group UK 2022-06-09 /pmc/articles/PMC9178220/ /pubmed/35681085 http://dx.doi.org/10.1038/s41598-022-13775-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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 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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Kang, Heewon
Min, Kyung-Duk
Jeon, Seonghee
Lee, Ju-Yeun
Cho, Sung-il
A measure to estimate the risk of imported COVID-19 cases and its application for evaluating travel-related control measures
title A measure to estimate the risk of imported COVID-19 cases and its application for evaluating travel-related control measures
title_full A measure to estimate the risk of imported COVID-19 cases and its application for evaluating travel-related control measures
title_fullStr A measure to estimate the risk of imported COVID-19 cases and its application for evaluating travel-related control measures
title_full_unstemmed A measure to estimate the risk of imported COVID-19 cases and its application for evaluating travel-related control measures
title_short A measure to estimate the risk of imported COVID-19 cases and its application for evaluating travel-related control measures
title_sort measure to estimate the risk of imported covid-19 cases and its application for evaluating travel-related control measures
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9178220/
https://www.ncbi.nlm.nih.gov/pubmed/35681085
http://dx.doi.org/10.1038/s41598-022-13775-0
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