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10.1016/j.chaos.2020.110036 http://scihub22266oqcxt.onion/10.1016/j.chaos.2020.110036 C7311924!7311924!32834596     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 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       Chaos+Solitons+Fractals 2020 ; 139 (ä): 110036 Nephropedia Template TP {{tp|p=32834596|t=2020. Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model |pdf=|usr=}}{{32834596}} gab.com Text Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model JO: Chaos Solitons Fractals http://www.kidney.de/pget.php?&tw=1&pmid=32834596 #FOAvip Similar to other epidemics, the novel coronavirus (COVID-19) spread very fast and infected almost two hundreds countries around the globe since December 2019. The unique characteristics of the COVID-19 include its ability of faster expansion through freely existed viruses or air molecules in the atmosphere. Assuming that the spread of virus follows a random process instead of deterministic. The continuous time Markov Chain (CTMC) through stochastic model approach has been utilized for predicting the impending states with the use of random variables. The proposed study is devoted to investigate a model consist of three exclusive compartments. The first class includes white nose based transmission rate (termed as susceptible individuals), the second one pertains to the infected population having the same perturbation occurrence and the last one isolated (quarantined) individuals. We discuss the model?s extinction as well as the stationary distribution in order to derive the the sufficient criterion for the persistence and disease? extinction. Lastly, the numerical simulation is executed for supporting the theoretical findings. Twit Text FOAVip Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model ????Chaos Solitons Fractals http://www.kidney.de/pget.php?&tw=1&pmid=32834596 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32834596 #FOAvip English Wikipedia <ref>{{Cite pmid|32834596}}</ref> Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model #MMPMID32834596 Din A; Khan A; Baleanu D Chaos Solitons Fractals 2020[Oct]; 139 (ä): 110036 PMID32834596show ga Similar to other epidemics, the novel coronavirus (COVID-19) spread very fast and infected almost two hundreds countries around the globe since December 2019. The unique characteristics of the COVID-19 include its ability of faster expansion through freely existed viruses or air molecules in the atmosphere. Assuming that the spread of virus follows a random process instead of deterministic. The continuous time Markov Chain (CTMC) through stochastic model approach has been utilized for predicting the impending states with the use of random variables. The proposed study is devoted to investigate a model consist of three exclusive compartments. The first class includes white nose based transmission rate (termed as susceptible individuals), the second one pertains to the infected population having the same perturbation occurrence and the last one isolated (quarantined) individuals. We discuss the model?s extinction as well as the stationary distribution in order to derive the the sufficient criterion for the persistence and disease? extinction. Lastly, the numerical simulation is executed for supporting the theoretical findings. äStationary distribution and extinction of stochastic coronavirus (COVI(epmc).pdf DeepDyve Pubget Overpricing