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The collaboration between infectious disease modeling and public health decision-making based on the COVID-19
Public health decision-making may have great uncertainty especially in dealing with emerging infectious diseases, so it is necessary to establish a collaborative mechanism among modelers, epidemiologists, and public health decision-makers to reduce the uncertainty as much as possible. We searched th...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8197614/ http://dx.doi.org/10.1016/j.jnlssr.2021.06.001 |
_version_ | 1783706958513045504 |
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author | Niu, Yan Li, Zhuoyang Meng, Ling Wang, Shengnan Zhao, Zeyu Song, Tie Lu, Jianhua Chen, Tianmu Li, Qun Zou, Xuan |
author_facet | Niu, Yan Li, Zhuoyang Meng, Ling Wang, Shengnan Zhao, Zeyu Song, Tie Lu, Jianhua Chen, Tianmu Li, Qun Zou, Xuan |
author_sort | Niu, Yan |
collection | PubMed |
description | Public health decision-making may have great uncertainty especially in dealing with emerging infectious diseases, so it is necessary to establish a collaborative mechanism among modelers, epidemiologists, and public health decision-makers to reduce the uncertainty as much as possible. We searched the relevant studies on transmission dynamics modeling of infectious diseases, SARS, MERS, and COVID-19 as of March 1, 2021 based on PubMed. We compared the key health decision-making time points of SARS, MERS, and COVID-19 prevention and control, and the publication time points of modeling research, to reveal the collaboration between infectious disease modeling and public health decision-making in the context of the COVID-19 pandemic. Searching with infectious disease and mathematical model as keywords, there were 166, 81 and 1 289 studies on the modeling of infectious disease transmission dynamics of SARS, MERS, and COVID-19 were retrieved respectively. Based on the modeling application framework of public health practice proposed in the current study, the collaboration among modelers, epidemiologists and public health decision-makers should be strengthened in the future. |
format | Online Article Text |
id | pubmed-8197614 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81976142021-06-15 The collaboration between infectious disease modeling and public health decision-making based on the COVID-19 Niu, Yan Li, Zhuoyang Meng, Ling Wang, Shengnan Zhao, Zeyu Song, Tie Lu, Jianhua Chen, Tianmu Li, Qun Zou, Xuan Journal of Safety Science and Resilience Article Public health decision-making may have great uncertainty especially in dealing with emerging infectious diseases, so it is necessary to establish a collaborative mechanism among modelers, epidemiologists, and public health decision-makers to reduce the uncertainty as much as possible. We searched the relevant studies on transmission dynamics modeling of infectious diseases, SARS, MERS, and COVID-19 as of March 1, 2021 based on PubMed. We compared the key health decision-making time points of SARS, MERS, and COVID-19 prevention and control, and the publication time points of modeling research, to reveal the collaboration between infectious disease modeling and public health decision-making in the context of the COVID-19 pandemic. Searching with infectious disease and mathematical model as keywords, there were 166, 81 and 1 289 studies on the modeling of infectious disease transmission dynamics of SARS, MERS, and COVID-19 were retrieved respectively. Based on the modeling application framework of public health practice proposed in the current study, the collaboration among modelers, epidemiologists and public health decision-makers should be strengthened in the future. China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. 2021-06 2021-06-12 /pmc/articles/PMC8197614/ http://dx.doi.org/10.1016/j.jnlssr.2021.06.001 Text en © 2022 China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Niu, Yan Li, Zhuoyang Meng, Ling Wang, Shengnan Zhao, Zeyu Song, Tie Lu, Jianhua Chen, Tianmu Li, Qun Zou, Xuan The collaboration between infectious disease modeling and public health decision-making based on the COVID-19 |
title | The collaboration between infectious disease modeling and public health decision-making based on the COVID-19 |
title_full | The collaboration between infectious disease modeling and public health decision-making based on the COVID-19 |
title_fullStr | The collaboration between infectious disease modeling and public health decision-making based on the COVID-19 |
title_full_unstemmed | The collaboration between infectious disease modeling and public health decision-making based on the COVID-19 |
title_short | The collaboration between infectious disease modeling and public health decision-making based on the COVID-19 |
title_sort | collaboration between infectious disease modeling and public health decision-making based on the covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8197614/ http://dx.doi.org/10.1016/j.jnlssr.2021.06.001 |
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