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The application framework of big data technology in the COVID-19 epidemic emergency management in local government—a case study of Hainan Province, China
BACKGROUND: As COVID-19 continues to spread globally, traditional emergency management measures are facing many practical limitations. The application of big data analysis technology provides an opportunity for local governments to conduct the COVID-19 epidemic emergency management more scientifical...
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/PMC8567122/ https://www.ncbi.nlm.nih.gov/pubmed/34736445 http://dx.doi.org/10.1186/s12889-021-12065-0 |
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author | Mao, Zijun Zou, Qi Yao, Hong Wu, Jingyi |
author_facet | Mao, Zijun Zou, Qi Yao, Hong Wu, Jingyi |
author_sort | Mao, Zijun |
collection | PubMed |
description | BACKGROUND: As COVID-19 continues to spread globally, traditional emergency management measures are facing many practical limitations. The application of big data analysis technology provides an opportunity for local governments to conduct the COVID-19 epidemic emergency management more scientifically. The present study, based on emergency management lifecycle theory, includes a comprehensive analysis of the application framework of China’s SARS epidemic emergency management lacked the support of big data technology in 2003. In contrast, this study first proposes a more agile and efficient application framework, supported by big data technology, for the COVID-19 epidemic emergency management and then analyses the differences between the two frameworks. METHODS: This study takes Hainan Province, China as its case study by using a file content analysis and semistructured interviews to systematically comprehend the strategy and mechanism of Hainan’s application of big data technology in its COVID-19 epidemic emergency management. RESULTS: Hainan Province adopted big data technology during the four stages, i.e., migration, preparedness, response, and recovery, of its COVID-19 epidemic emergency management. Hainan Province developed advanced big data management mechanisms and technologies for practical epidemic emergency management, thereby verifying the feasibility and value of the big data technology application framework we propose. CONCLUSIONS: This study provides empirical evidence for certain aspects of the theory, mechanism, and technology for local governments in different countries and regions to apply, in a precise, agile, and evidence-based manner, big data technology in their formulations of comprehensive COVID-19 epidemic emergency management strategies. |
format | Online Article Text |
id | pubmed-8567122 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-85671222021-11-04 The application framework of big data technology in the COVID-19 epidemic emergency management in local government—a case study of Hainan Province, China Mao, Zijun Zou, Qi Yao, Hong Wu, Jingyi BMC Public Health Research BACKGROUND: As COVID-19 continues to spread globally, traditional emergency management measures are facing many practical limitations. The application of big data analysis technology provides an opportunity for local governments to conduct the COVID-19 epidemic emergency management more scientifically. The present study, based on emergency management lifecycle theory, includes a comprehensive analysis of the application framework of China’s SARS epidemic emergency management lacked the support of big data technology in 2003. In contrast, this study first proposes a more agile and efficient application framework, supported by big data technology, for the COVID-19 epidemic emergency management and then analyses the differences between the two frameworks. METHODS: This study takes Hainan Province, China as its case study by using a file content analysis and semistructured interviews to systematically comprehend the strategy and mechanism of Hainan’s application of big data technology in its COVID-19 epidemic emergency management. RESULTS: Hainan Province adopted big data technology during the four stages, i.e., migration, preparedness, response, and recovery, of its COVID-19 epidemic emergency management. Hainan Province developed advanced big data management mechanisms and technologies for practical epidemic emergency management, thereby verifying the feasibility and value of the big data technology application framework we propose. CONCLUSIONS: This study provides empirical evidence for certain aspects of the theory, mechanism, and technology for local governments in different countries and regions to apply, in a precise, agile, and evidence-based manner, big data technology in their formulations of comprehensive COVID-19 epidemic emergency management strategies. BioMed Central 2021-11-04 /pmc/articles/PMC8567122/ /pubmed/34736445 http://dx.doi.org/10.1186/s12889-021-12065-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Mao, Zijun Zou, Qi Yao, Hong Wu, Jingyi The application framework of big data technology in the COVID-19 epidemic emergency management in local government—a case study of Hainan Province, China |
title | The application framework of big data technology in the COVID-19 epidemic emergency management in local government—a case study of Hainan Province, China |
title_full | The application framework of big data technology in the COVID-19 epidemic emergency management in local government—a case study of Hainan Province, China |
title_fullStr | The application framework of big data technology in the COVID-19 epidemic emergency management in local government—a case study of Hainan Province, China |
title_full_unstemmed | The application framework of big data technology in the COVID-19 epidemic emergency management in local government—a case study of Hainan Province, China |
title_short | The application framework of big data technology in the COVID-19 epidemic emergency management in local government—a case study of Hainan Province, China |
title_sort | application framework of big data technology in the covid-19 epidemic emergency management in local government—a case study of hainan province, china |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8567122/ https://www.ncbi.nlm.nih.gov/pubmed/34736445 http://dx.doi.org/10.1186/s12889-021-12065-0 |
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