Science & Technology Review
|
2020, 38(6): 83-89
• Papers •
Application of empirical data assimilation method in trend analysis of COVID-19
Full
YUAN Hongyong1, LIANG Manchun1, HUANG Quanyi1, SU Guofeng1, CHEN Tao1, CHEN Jianguo1, SUN Zhanhui1, YANG Sihang1, DENG Lizheng1, LI Ke1, QIN Zesheng2, YU Miaomiao1, CHENG Ming1, LI Kaiyuan1, LIU Gang1, XIAO Xinxin2, LI Wenzhang2
Affiliations
1. Department of Engineering Physics, Tsinghua University, Beijing 100094, China;
2. Environmental Safety Business Division, Beijing Safety Technology, Co., Ltd., Beijing 100094, China
Published: 2020-03-28
doi: 10.3981/j.issn.1000-7857.2020.06.012
Outline
The method of "empirical data assimilation for the SARS epidemic trend model" is used to assimilate the model parameters based on the new crown epidemic data released by the Health Committee of each city, and our research team's recent work is presented, including the multiple epidemic trend analysis and the decision-making suggestions for the whole country (except Hubei), Hubei Province (except Wuhan) and Wuhan city from February 3 to February 28, 2020. Three prediction curves are shown as the guideline of the epidemic prevention and control to predict the development of the epidemic. The epidemic peak line of the model can be used as a standard line to evaluate whether the current epidemic prevention measures are appropriate and be used for the early warning of the epidemic trend in various cities, to guide the proper taking of the epidemic prevention measures, to provide the decision support for the scheduling of medical resources and emergency supplies for life, and to play a role in stabilizing the public mood.
COVID-19
/
epidemic prediction curves
/
early warning of epidemic trend
YUAN Hongyong, LIANG Manchun, HUANG Quanyi, SU Guofeng, CHEN Tao, CHEN Jianguo, SUN Zhanhui, YANG Sihang, DENG Lizheng, LI Ke, QIN Zesheng, YU Miaomiao, CHENG Ming, LI Kaiyuan, LIU Gang, XIAO Xinxin, LI Wenzhang.
Application of empirical data assimilation method in trend analysis of COVID-19[J].
Science & Technology Review,
2020
, 38
(6)
: 83
-89
.
DOI: 10.3981/j.issn.1000-7857.2020.06.012
Year 2020 volume 38 Issue 6
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Article Info
doi: 10.3981/j.issn.1000-7857.2020.06.012
- Receive Date:2020-02-29
- Online Date:2020-05-11
- Published:2020-03-28