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10.1038/s41598-021-91024-6 http://scihub22266oqcxt.onion/10.1038/s41598-021-91024-6 34108505!8190287!34108505     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       Sci+Rep 2021 ; 11 (1): 12177 Nephropedia Template TP {{tp|p=34108505|t=2021. Dynamics based on analysis of public data for spreading of disease |pdf=|usr=}}{{34108505}} gab.com Text Dynamics based on analysis of public data for spreading of disease JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=34108505 #FOAvip The stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supply by the public health agencies in countries as Brazil, United States and India is investigated. We perform a numerical analysis using the stochastic differential equation in Ito's calculus for the estimating of novel cases daily, as well as analytical calculations solving the correspondent Fokker-Planck equation for the probability density distribution of novel cases, P(N(t), t). Our results display that the model based in the Ito's diffusion fits well to the results due to uncertainty in the official data and to the number of tests realized in populations of each country. Twit Text FOAVip Dynamics based on analysis of public data for spreading of disease ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=34108505 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34108505 #FOAvip English Wikipedia <ref>{{Cite pmid|34108505}}</ref> Dynamics based on analysis of public data for spreading of disease #MMPMID34108505 Lima LS Sci Rep 2021[Jun]; 11 (1): 12177 PMID34108505show ga The stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supply by the public health agencies in countries as Brazil, United States and India is investigated. We perform a numerical analysis using the stochastic differential equation in Ito's calculus for the estimating of novel cases daily, as well as analytical calculations solving the correspondent Fokker-Planck equation for the probability density distribution of novel cases, P(N(t), t). Our results display that the model based in the Ito's diffusion fits well to the results due to uncertainty in the official data and to the number of tests realized in populations of each country. |*Databases, Factual[MESH] |*Models, Statistical[MESH] |COVID-19/*epidemiology/*transmission[MESH] |Humans[MESH] |Stochastic Processes[MESH]Dynamics based on analysis of public data for spreading of disease (epmc).pdf DeepDyve Pubget Overpricing