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10.1016/j.meegid.2020.104306 http://scihub22266oqcxt.onion/10.1016/j.meegid.2020.104306 32278147!7141629!32278147     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Infect+Genet+Evol 2020 ; 82 (ä): 104306 Nephropedia Template TP {{tp|p=32278147|t=2020. Mathematical model of infection kinetics and its analysis for COVID-19, SARS and MERS |pdf=|usr=}}{{32278147}} gab.com Text Mathematical model of infection kinetics and its analysis for COVID-19, SARS and MERS JO: Infect Genet Evol http://www.kidney.de/pget.php?&tw=1&pmid=32278147 #FOAvip The purpose of this paper is to reveal the spread rules of the three pneumonia: COVID-19, SARS and MERS. We compare the new spread characteristics of COVID-19 with those of SARS and MERS. By considering the growth rate and inhibition constant of infectious diseases, their propagation growth model is established. The parameters of the three coronavirus transmission growth models are obtained by nonlinear fitting. Parametric analysis shows that the growth rate of COVID-19 is about twice that of the SARS and MERS, and the COVID-19 doubling cycle is two to three days, suggesting that the number of COVID-19 patients would double in two to three days without human intervention. The infection inhibition constant in Hubei is two orders of magnitude lower than in other regions, which reasonably explains the situation of the COVID-19 outbreak in Hubei. Twit Text FOAVip Mathematical model of infection kinetics and its analysis for COVID-19, SARS and MERS ????Infect Genet Evol http://www.kidney.de/pget.php?&tw=1&pmid=32278147 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32278147 #FOAvip English Wikipedia <ref>{{Cite pmid|32278147}}</ref> Mathematical model of infection kinetics and its analysis for COVID-19, SARS and MERS #MMPMID32278147 Liang K Infect Genet Evol 2020[Aug]; 82 (ä): 104306 PMID32278147show ga The purpose of this paper is to reveal the spread rules of the three pneumonia: COVID-19, SARS and MERS. We compare the new spread characteristics of COVID-19 with those of SARS and MERS. By considering the growth rate and inhibition constant of infectious diseases, their propagation growth model is established. The parameters of the three coronavirus transmission growth models are obtained by nonlinear fitting. Parametric analysis shows that the growth rate of COVID-19 is about twice that of the SARS and MERS, and the COVID-19 doubling cycle is two to three days, suggesting that the number of COVID-19 patients would double in two to three days without human intervention. The infection inhibition constant in Hubei is two orders of magnitude lower than in other regions, which reasonably explains the situation of the COVID-19 outbreak in Hubei. |*Models, Biological[MESH] |Betacoronavirus/*growth & development/physiology[MESH] |COVID-19[MESH] |China/epidemiology[MESH] |Communicable Disease Control[MESH] |Coronavirus Infections/*epidemiology/transmission/virology[MESH] |Hong Kong/epidemiology[MESH] |Humans[MESH] |Middle East Respiratory Syndrome Coronavirus/*growth & development/physiology[MESH] |Pandemics[MESH] |Pneumonia, Viral/*epidemiology/transmission/virology[MESH] |SARS-CoV-2[MESH] |Saudi Arabia/epidemiology[MESH]Mathematical model of infection kinetics and its analysis for COVID-19(epmc).pdf DeepDyve Pubget Overpricing