Niu Yan, Li Zhuoyang, Meng Ling, Wang Shengnan, Zhao Zeyu, Song Tie, Lu Jianhua, Chen Tianmu, Li Qun, Zou Xuan
Public Health Emergency Center, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian, 361005, China.
J Saf Sci Resil. 2021 Jun;2(2):69-76. doi: 10.1016/j.jnlssr.2021.06.001. Epub 2021 Jun 12.
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.
公共卫生决策可能具有很大的不确定性，尤其是在应对新发传染病时，因此有必要在建模人员、流行病学家和公共卫生决策者之间建立协作机制，以尽可能降低不确定性。我们基于PubMed搜索了截至2021年3月1日有关传染病、SARS、MERS和COVID-19传播动力学建模的相关研究。我们比较了SARS、MERS和COVID-19防控的关键卫生决策时间点以及建模研究的发表时间点，以揭示在COVID-19大流行背景下传染病建模与公共卫生决策之间的协作。以传染病和数学模型为关键词进行搜索，分别检索到166项、81项和1289项关于SARS、MERS和COVID-19传染病传播动力学建模的研究。基于本研究提出的公共卫生实践建模应用框架，未来应加强建模人员、流行病学家和公共卫生决策者之间的协作。
