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10.1016/j.scitotenv.2020.138834 http://scihub22266oqcxt.onion/10.1016/j.scitotenv.2020.138834 32334161!7194615!32334161     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 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+Total+Environ 2020 ; 728 (ä): 138834 Nephropedia Template TP {{tp|p=32334161|t=2020. Can we predict the occurrence of COVID-19 cases? Considerations using a simple model of growth |pdf=|usr=}}{{32334161}} gab.com Text Can we predict the occurrence of COVID-19 cases Considerations using a simple model of growth JO: Sci Total Environ http://www.kidney.de/pget.php?&tw=1&pmid=32334161 #FOAvip This study aimed to present a simple model to follow the evolution of the COVID-19 (CV-19) pandemic in different countries. The cumulative distribution function (CDF) and its first derivative were employed for this task. The simulations showed that it is almost impossible to predict based on the initial CV-19 cases (1st 2nd or 3rd weeks) how the pandemic will evolve. However, the results presented here revealed that this approach can be used as an alternative for the exponential growth model, traditionally employed as a prediction model, and serve as a valuable tool for investigating how protective measures are changing the evolution of the pandemic. Twit Text FOAVip Can we predict the occurrence of COVID-19 cases Considerations using a simple model of growth ????Sci Total Environ http://www.kidney.de/pget.php?&tw=1&pmid=32334161 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32334161 #FOAvip English Wikipedia <ref>{{Cite pmid|32334161}}</ref> Can we predict the occurrence of COVID-19 cases? Considerations using a simple model of growth #MMPMID32334161 Cassaro FAM; Pires LF Sci Total Environ 2020[Aug]; 728 (ä): 138834 PMID32334161show ga This study aimed to present a simple model to follow the evolution of the COVID-19 (CV-19) pandemic in different countries. The cumulative distribution function (CDF) and its first derivative were employed for this task. The simulations showed that it is almost impossible to predict based on the initial CV-19 cases (1st 2nd or 3rd weeks) how the pandemic will evolve. However, the results presented here revealed that this approach can be used as an alternative for the exponential growth model, traditionally employed as a prediction model, and serve as a valuable tool for investigating how protective measures are changing the evolution of the pandemic. |*Models, Theoretical[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Computer Simulation[MESH] |Coronavirus Infections/*epidemiology[MESH] |Forecasting/*methods[MESH] |Humans[MESH] |Pandemics[MESH] |Pneumonia, Viral/*epidemiology[MESH]Can we predict the occurrence of COVID-19 cases? Considerations using (epmc).pdf DeepDyve Pubget Overpricing