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Assessment of the impact of reopening strategies on the spatial transmission risk of COVID-19 based on a data-driven transmission model

COVID-19 has dramatically changed people's mobility geste patterns and affected the operations of different functional spots. In the environment of the successful reopening of countries around the world since 2022, it's pivotal to understand whether the reopening of different types of loca...

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Autores principales: Wang, Jing, Huang, YuHui, Dong, Ying, Wu, BingYing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10333357/
https://www.ncbi.nlm.nih.gov/pubmed/37429885
http://dx.doi.org/10.1038/s41598-023-37297-5
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author Wang, Jing
Huang, YuHui
Dong, Ying
Wu, BingYing
author_facet Wang, Jing
Huang, YuHui
Dong, Ying
Wu, BingYing
author_sort Wang, Jing
collection PubMed
description COVID-19 has dramatically changed people's mobility geste patterns and affected the operations of different functional spots. In the environment of the successful reopening of countries around the world since 2022, it's pivotal to understand whether the reopening of different types of locales poses a threat of wide epidemic transmission. In this paper, by establishing an epidemiological model based on mobile network data, combining the data handed by the Safegraph website, and taking into account the crowd inflow characteristics and the changes of susceptible and latent populations, the trends of the number of crowd visits and the number of epidemic infections at different functional points of interest after the perpetration of continuing strategies were simulated. The model was also validated with daily new cases in ten metropolitan areas in the United States from March to May 2020, and the results showed that the model fitted the evolutionary trend of realistic data more accurately. Further, the points of interest were classified into risk levels, and the corresponding reopening minimum standard prevention and control measures were proposed to be implemented according to different risk levels. The results showed that restaurants and gyms became high-risk points of interest after the perpetration of the continuing strategy, especially the general dine-in restaurants were at higher risk levels. Religious exertion centers were the points of interest with the loftiest average infection rates after the perpetration of the continuing strategy. Points of interest such as convenience stores, large shopping malls, and pharmacies were at a lower risk for outbreak impact after the continuing strategy was enforced. Based on this, continuing forestallment and control strategies for different functional points of interest are proposed to provide decision support for the development of precise forestallment and control measures for different spots.
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spelling pubmed-103333572023-07-12 Assessment of the impact of reopening strategies on the spatial transmission risk of COVID-19 based on a data-driven transmission model Wang, Jing Huang, YuHui Dong, Ying Wu, BingYing Sci Rep Article COVID-19 has dramatically changed people's mobility geste patterns and affected the operations of different functional spots. In the environment of the successful reopening of countries around the world since 2022, it's pivotal to understand whether the reopening of different types of locales poses a threat of wide epidemic transmission. In this paper, by establishing an epidemiological model based on mobile network data, combining the data handed by the Safegraph website, and taking into account the crowd inflow characteristics and the changes of susceptible and latent populations, the trends of the number of crowd visits and the number of epidemic infections at different functional points of interest after the perpetration of continuing strategies were simulated. The model was also validated with daily new cases in ten metropolitan areas in the United States from March to May 2020, and the results showed that the model fitted the evolutionary trend of realistic data more accurately. Further, the points of interest were classified into risk levels, and the corresponding reopening minimum standard prevention and control measures were proposed to be implemented according to different risk levels. The results showed that restaurants and gyms became high-risk points of interest after the perpetration of the continuing strategy, especially the general dine-in restaurants were at higher risk levels. Religious exertion centers were the points of interest with the loftiest average infection rates after the perpetration of the continuing strategy. Points of interest such as convenience stores, large shopping malls, and pharmacies were at a lower risk for outbreak impact after the continuing strategy was enforced. Based on this, continuing forestallment and control strategies for different functional points of interest are proposed to provide decision support for the development of precise forestallment and control measures for different spots. Nature Publishing Group UK 2023-07-10 /pmc/articles/PMC10333357/ /pubmed/37429885 http://dx.doi.org/10.1038/s41598-023-37297-5 Text en © The Author(s) 2023 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
Wang, Jing
Huang, YuHui
Dong, Ying
Wu, BingYing
Assessment of the impact of reopening strategies on the spatial transmission risk of COVID-19 based on a data-driven transmission model
title Assessment of the impact of reopening strategies on the spatial transmission risk of COVID-19 based on a data-driven transmission model
title_full Assessment of the impact of reopening strategies on the spatial transmission risk of COVID-19 based on a data-driven transmission model
title_fullStr Assessment of the impact of reopening strategies on the spatial transmission risk of COVID-19 based on a data-driven transmission model
title_full_unstemmed Assessment of the impact of reopening strategies on the spatial transmission risk of COVID-19 based on a data-driven transmission model
title_short Assessment of the impact of reopening strategies on the spatial transmission risk of COVID-19 based on a data-driven transmission model
title_sort assessment of the impact of reopening strategies on the spatial transmission risk of covid-19 based on a data-driven transmission model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10333357/
https://www.ncbi.nlm.nih.gov/pubmed/37429885
http://dx.doi.org/10.1038/s41598-023-37297-5
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