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Application of Pandemic Intelligence in Dynamic Data in Taiwan
Taiwan was successful in containing the spread of the novel coronavirus (COVID-19) in 2020. One major factor in this success was the compilation and provision of comprehensive information about the pandemic. The present study proposes a pandemic intelligence system that provides data on the number o...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8467998/ https://www.ncbi.nlm.nih.gov/pubmed/34574847 http://dx.doi.org/10.3390/ijerph18189925 |
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author | Chang, Tzu-Yin Su, Wen-Ray Chen, Hongey Huang, Ming-Wey Chen, Lu-Yen A. |
author_facet | Chang, Tzu-Yin Su, Wen-Ray Chen, Hongey Huang, Ming-Wey Chen, Lu-Yen A. |
author_sort | Chang, Tzu-Yin |
collection | PubMed |
description | Taiwan was successful in containing the spread of the novel coronavirus (COVID-19) in 2020. One major factor in this success was the compilation and provision of comprehensive information about the pandemic. The present study proposes a pandemic intelligence system that provides data on the number of epidemic prevention professionals in each county and city, as well as daily confirmed cases, the demographics of the confirmed cases, and available resources (negative-pressure room beds and artificial ventilation apparatuses) in hospitals. Furthermore, the system provides the location of pharmacies selling masks and their current inventories, as well as the distribution of crowds at popular tourist destinations and social-distance monitoring. The most frequently used map layer in the thematic map of the pandemic is that of crowd distribution during the study period from March 2020 until the end of the same year. The case study used in this investigation for applying the system is represented by the 4-day weekend for Tomb-Sweeping Day of 2020. Through the real-time analysis of dynamic data and the integration of intelligence, the system offers a clear insight into changes in relevant information and, thus, enables the preemptive deployment of control measures by the county/city governments regarding pandemic management. |
format | Online Article Text |
id | pubmed-8467998 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-84679982021-09-27 Application of Pandemic Intelligence in Dynamic Data in Taiwan Chang, Tzu-Yin Su, Wen-Ray Chen, Hongey Huang, Ming-Wey Chen, Lu-Yen A. Int J Environ Res Public Health Article Taiwan was successful in containing the spread of the novel coronavirus (COVID-19) in 2020. One major factor in this success was the compilation and provision of comprehensive information about the pandemic. The present study proposes a pandemic intelligence system that provides data on the number of epidemic prevention professionals in each county and city, as well as daily confirmed cases, the demographics of the confirmed cases, and available resources (negative-pressure room beds and artificial ventilation apparatuses) in hospitals. Furthermore, the system provides the location of pharmacies selling masks and their current inventories, as well as the distribution of crowds at popular tourist destinations and social-distance monitoring. The most frequently used map layer in the thematic map of the pandemic is that of crowd distribution during the study period from March 2020 until the end of the same year. The case study used in this investigation for applying the system is represented by the 4-day weekend for Tomb-Sweeping Day of 2020. Through the real-time analysis of dynamic data and the integration of intelligence, the system offers a clear insight into changes in relevant information and, thus, enables the preemptive deployment of control measures by the county/city governments regarding pandemic management. MDPI 2021-09-21 /pmc/articles/PMC8467998/ /pubmed/34574847 http://dx.doi.org/10.3390/ijerph18189925 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chang, Tzu-Yin Su, Wen-Ray Chen, Hongey Huang, Ming-Wey Chen, Lu-Yen A. Application of Pandemic Intelligence in Dynamic Data in Taiwan |
title | Application of Pandemic Intelligence in Dynamic Data in Taiwan |
title_full | Application of Pandemic Intelligence in Dynamic Data in Taiwan |
title_fullStr | Application of Pandemic Intelligence in Dynamic Data in Taiwan |
title_full_unstemmed | Application of Pandemic Intelligence in Dynamic Data in Taiwan |
title_short | Application of Pandemic Intelligence in Dynamic Data in Taiwan |
title_sort | application of pandemic intelligence in dynamic data in taiwan |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8467998/ https://www.ncbi.nlm.nih.gov/pubmed/34574847 http://dx.doi.org/10.3390/ijerph18189925 |
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