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10.1002/mma.6345 http://scihub22266oqcxt.onion/10.1002/mma.6345 32327866!7168448!32327866     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Math+Methods+Appl+Sci 2020 ; 43 (7): 4943-4949 Nephropedia Template TP {{tp|p=32327866|t=2020. Dynamic models for Coronavirus Disease 2019 and data analysis |pdf=|usr=}}{{32327866}} gab.com Text Dynamic models for Coronavirus Disease 2019 and data analysis JO: Math Methods Appl Sci http://www.kidney.de/pget.php?&tw=1&pmid=32327866 #FOAvip In this letter, two time delay dynamic models, a Time Delay Dynamical-Novel Coronavirus Pneumonia (TDD-NCP) model and Fudan-Chinese Center for Disease Control and Prevention (CCDC) model, are introduced to track the data of Coronavirus Disease 2019 (COVID-19). The TDD-NCP model was developed recently by Chengars group in Fudan and Shanghai University of Finance and Economics (SUFE). The TDD-NCP model introduced the time delay process into the differential equations to describe the latent period of the epidemic. The Fudan-CDCC model was established when Wenbin Chen suggested to determine the kernel functions in the TDD-NCP model by the public data from CDCC. By the public data of the cumulative confirmed cases in different regions in China and different countries, these models can clearly illustrate that the containment of the epidemic highly depends on early and effective isolations. Twit Text FOAVip Dynamic models for Coronavirus Disease 2019 and data analysis ????Math Methods Appl Sci http://www.kidney.de/pget.php?&tw=1&pmid=32327866 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32327866 #FOAvip English Wikipedia <ref>{{Cite pmid|32327866}}</ref> Dynamic models for Coronavirus Disease 2019 and data analysis #MMPMID32327866 Shao N; Zhong M; Yan Y; Pan H; Cheng J; Chen W Math Methods Appl Sci 2020[May]; 43 (7): 4943-4949 PMID32327866show ga In this letter, two time delay dynamic models, a Time Delay Dynamical-Novel Coronavirus Pneumonia (TDD-NCP) model and Fudan-Chinese Center for Disease Control and Prevention (CCDC) model, are introduced to track the data of Coronavirus Disease 2019 (COVID-19). The TDD-NCP model was developed recently by Chengars group in Fudan and Shanghai University of Finance and Economics (SUFE). The TDD-NCP model introduced the time delay process into the differential equations to describe the latent period of the epidemic. The Fudan-CDCC model was established when Wenbin Chen suggested to determine the kernel functions in the TDD-NCP model by the public data from CDCC. By the public data of the cumulative confirmed cases in different regions in China and different countries, these models can clearly illustrate that the containment of the epidemic highly depends on early and effective isolations. äDynamic models for Coronavirus Disease 2019 and data analysis (epmc).pdf DeepDyve Pubget Overpricing