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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...

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Autores principales: Niu, Yan, Li, Zhuoyang, Meng, Ling, Wang, Shengnan, Zhao, Zeyu, Song, Tie, Lu, Jianhua, Chen, Tianmu, Li, Qun, Zou, Xuan
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
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8197614/
http://dx.doi.org/10.1016/j.jnlssr.2021.06.001
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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.
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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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