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10.1371/journal.pone.0245728 http://scihub22266oqcxt.onion/10.1371/journal.pone.0245728 33735225!7971534!33735225     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       PLoS+One 2021 ; 16 (3): e0245728 Nephropedia Template TP {{tp|p=33735225|t=2021. Analysis of the real number of infected people by COVID-19: A system dynamics approach |pdf=|usr=}}{{33735225}} gab.com Text Analysis of the real number of infected people by COVID-19: A system dynamics approach JO: PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=33735225 #FOAvip 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. Twit Text FOAVip Analysis of the real number of infected people by COVID-19: A system dynamics approach ????PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=33735225 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33735225 #FOAvip English Wikipedia <ref>{{Cite pmid|33735225}}</ref> Analysis of the real number of infected people by COVID-19: A system dynamics approach #MMPMID33735225 Hu B; Dehmer M; Emmert-Streib F; Zhang B PLoS One 2021[]; 16 (3): e0245728 PMID33735225show ga 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. |Algorithms[MESH] |COVID-19/*epidemiology/prevention & control/transmission[MESH] |China/epidemiology[MESH] |Humans[MESH] |Models, Statistical[MESH] |Monte Carlo Method[MESH] |Pandemics[MESH] |Quarantine[MESH] |SARS-CoV-2/isolation & purification[MESH]Analysis of the real number of infected people by COVID-19: A system d(epmc).pdf DeepDyve Pubget Overpricing