Analysis of the real number of infected people by COVID-19: A system dynamics approach

被引:6
|
作者
Hu, Bo [1 ]
Dehmer, Matthias [2 ,3 ,4 ,5 ]
Emmert-Streib, Frank [6 ,7 ]
Zhang, Bo [8 ]
机构
[1] Univ Bundeswehr Munchen, Dept Business Adm, Neubiberg, Germany
[2] Swiss Distance Univ Appl Sci, Dept Comp Sci, Brig, Switzerland
[3] Xian Technol Univ, Sch Sci, Xian, Shaanxi, Peoples R China
[4] Nankai Univ, Coll Artificial Intelligence, Tianjin, Peoples R China
[5] UMIT, Dept Biomed Comp Sci & Mechatron, Hlth & Life Sci Univ, Hall In Tirol, Austria
[6] Tampere Univ, Dept Signal Proc, Predict Med & Data Analyt Lab, Tampere, Finland
[7] Inst Biosci & Med Technol, Tampere, Finland
[8] Minist Ecol & Environm, Informat Ctr, Beijing, Peoples R China
来源
PLOS ONE | 2021年 / 16卷 / 03期
基金
奥地利科学基金会;
关键词
D O I
10.1371/journal.pone.0245728
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
At the beginning of 2020, the COVID-19 pandemic was able to spread quickly in Wuhan and in the province of Hubei due to a lack of experience with this novel virus. Additionally, authories had no proven experience with applying insufficient medical, communication and crisis management tools. For a considerable period of time, the actual number of people infected was unknown. There were great uncertainties regarding the dynamics and spread of the Covid-19 virus infection. In this paper, we develop a system dynamics model for the three connected regions (Wuhan, Hubei excl. Wuhan, China excl. Hubei) to understand the infection and spread dynamics of the virus and provide a more accurate estimate of the number of infected people in Wuhan and discuss the necessity and effectivity of protective measures against this epidemic, such as the quarantines imposed throughout China. We use the statistics of confirmed cases of China excl. Hubei. Also the daily data on travel activity within China was utilized, in order to determine the actual numerical development of the infected people in Wuhan City and Hubei Province. We used a multivariate Monte Carlo optimization to parameterize the model to match the official statistics. In particular, we used the model to calculate the infections, which had already broken out, but were not diagnosed for various reasons.
引用
收藏
页数:9
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