Article ; Online: Analysis of the real number of infected people by COVID-19: A system dynamics approach.
PloS one
2021 Volume 16, Issue 3, Page(s) e0245728
Abstract: ... regarding the dynamics and spread of the Covid-19 virus infection. In this paper, we develop a system ... the infection and spread dynamics of the virus and provide a more accurate estimate of the number of infected ... period of time, the actual number of people infected was unknown. There were great uncertainties ...
Abstract | 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. |
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MeSH term(s) | Algorithms ; COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19/transmission ; China/epidemiology ; Humans ; Models, Statistical ; Monte Carlo Method ; Pandemics ; Quarantine ; SARS-CoV-2/isolation & purification ; Travel |
Language | English |
Publishing date | 2021-03-18 |
Publishing country | United States |
Document type | Journal Article ; Research Support, Non-U.S. Gov't |
ISSN | 1932-6203 |
ISSN (online) | 1932-6203 |
DOI | 10.1371/journal.pone.0245728 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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