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10.1016/j.arcontrol.2021.01.006 http://scihub22266oqcxt.onion/10.1016/j.arcontrol.2021.01.006 33623479!7891093!33623479     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 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Annu+Rev+Control 2021 ; 51 (ä): 477-487 Nephropedia Template TP {{tp|p=33623479|t=2021. On an interval prediction of COVID-19 development based on a SEIR epidemic model |pdf=|usr=}}{{33623479}} gab.com Text On an interval prediction of COVID-19 development based on a SEIR epidemic model JO: Annu Rev Control http://www.kidney.de/pget.php?&tw=1&pmid=33623479 #FOAvip In this paper, a new version of the well-known epidemic mathematical SEIR model is used to analyze the pandemic course of COVID-19 in eight different countries. One of the proposed model's improvements is to reflect the societal feedback on the disease and confinement features. The SEIR model parameters are allowed to be time-varying, and the ranges of their values are identified by using publicly available data for France, Italy, Spain, Germany, Brazil, Russia, New York State (US), and China. The identified model is then applied to predict the SARS-CoV-2 virus propagation under various conditions of confinement. For this purpose, an interval predictor is designed, allowing variations and uncertainties in the model parameters to be taken into account. The code and the utilized data are available on Github. Twit Text FOAVip On an interval prediction of COVID-19 development based on a SEIR epidemic model ????Annu Rev Control http://www.kidney.de/pget.php?&tw=1&pmid=33623479 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33623479 #FOAvip English Wikipedia <ref>{{Cite pmid|33623479}}</ref> On an interval prediction of COVID-19 development based on a SEIR epidemic model #MMPMID33623479 Efimov D; Ushirobira R Annu Rev Control 2021[]; 51 (ä): 477-487 PMID33623479show ga In this paper, a new version of the well-known epidemic mathematical SEIR model is used to analyze the pandemic course of COVID-19 in eight different countries. One of the proposed model's improvements is to reflect the societal feedback on the disease and confinement features. The SEIR model parameters are allowed to be time-varying, and the ranges of their values are identified by using publicly available data for France, Italy, Spain, Germany, Brazil, Russia, New York State (US), and China. The identified model is then applied to predict the SARS-CoV-2 virus propagation under various conditions of confinement. For this purpose, an interval predictor is designed, allowing variations and uncertainties in the model parameters to be taken into account. The code and the utilized data are available on Github. äOn an interval prediction of COVID-19 development based on a SEIR epid(epmc).pdf DeepDyve Pubget Overpricing