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10.37757/MR2020.V22.N3.8 http://scihub22266oqcxt.onion/10.37757/MR2020.V22.N3.8 32812897!ä!32812897 Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32812897&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 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       MEDICC+Rev 2020 ; 22 (3): 32-39 Nephropedia Template TP {{tp|p=32812897|t=2020. COVID-19 Forecasts for Cuba Using Logistic Regression and Gompertz Curves |pdf=|usr=}}{{32812897}} gab.com Text COVID-19 Forecasts for Cuba Using Logistic Regression and Gompertz Curves JO: MEDICC Rev http://www.kidney.de/pget.php?&tw=1&pmid=32812897 #FOAvip INTRODUCTION On March 11, 2020, WHO declared COVID-19 a pandemic and called on governments to impose drastic measures to fi ght it. It is vitally important for government health authorities and leaders to have reliable estimates of infected cases and deaths in order to apply the necessary measures with the resources at their disposal. OBJECTIVE Test the validity of the logistic regression and Gompertz curve to forecast peaks of confi rmed cases and deaths in Cuba, as well as total number of cases. METHODS An inferential, predictive study was conducted using lo-gistic and Gompertz growth curves, adjusted with the least squares method and informatics tools for analysis and prediction of growth in COVID-19 cases and deaths. Italy and Spain-countries that have passed the initial peak of infection rates-were studied, and it was inferred from the results of these countries that their models were ap-plicable to Cuba. This hypothesis was tested by applying goodness-of-fi t and signifi cance tests on its parameters.RESULTS Both models showed good fi t, low mean square errors, and all parameters were highly signifi cant. CONCLUSIONS The validity of models was confi rmed based on logis-tic regression and the Gompertz curve to forecast the dates of peak infections and deaths, as well as total number of cases in Cuba. KEYWORDS COVID-19, SARS-CoV-2, logistic models, pandemic, mortality, Cuba. Twit Text FOAVip COVID-19 Forecasts for Cuba Using Logistic Regression and Gompertz Curves ????MEDICC Rev http://www.kidney.de/pget.php?&tw=1&pmid=32812897 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32812897 #FOAvip English Wikipedia <ref>{{Cite pmid|32812897}}</ref> COVID-19 Forecasts for Cuba Using Logistic Regression and Gompertz Curves #MMPMID32812897 Medina-Mendieta JF; Cortes-Cortes M; Cortes-Iglesias M MEDICC Rev 2020[Jul]; 22 (3): 32-39 PMID32812897show ga INTRODUCTION On March 11, 2020, WHO declared COVID-19 a pandemic and called on governments to impose drastic measures to fi ght it. It is vitally important for government health authorities and leaders to have reliable estimates of infected cases and deaths in order to apply the necessary measures with the resources at their disposal. OBJECTIVE Test the validity of the logistic regression and Gompertz curve to forecast peaks of confi rmed cases and deaths in Cuba, as well as total number of cases. METHODS An inferential, predictive study was conducted using lo-gistic and Gompertz growth curves, adjusted with the least squares method and informatics tools for analysis and prediction of growth in COVID-19 cases and deaths. Italy and Spain-countries that have passed the initial peak of infection rates-were studied, and it was inferred from the results of these countries that their models were ap-plicable to Cuba. This hypothesis was tested by applying goodness-of-fi t and signifi cance tests on its parameters.RESULTS Both models showed good fi t, low mean square errors, and all parameters were highly signifi cant. CONCLUSIONS The validity of models was confi rmed based on logis-tic regression and the Gompertz curve to forecast the dates of peak infections and deaths, as well as total number of cases in Cuba. KEYWORDS COVID-19, SARS-CoV-2, logistic models, pandemic, mortality, Cuba. |*Logistic Models[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Coronavirus Infections/*epidemiology[MESH] |Cuba/epidemiology[MESH] |Forecasting/*methods[MESH] |Humans[MESH] |Italy/epidemiology[MESH] |Pandemics[MESH] |Pneumonia, Viral/*epidemiology[MESH] |SARS-CoV-2[MESH]COVID-19 Forecasts for Cuba Using Logistic Regression and Gompertz Cur(epmc).pdf DeepDyve Pubget Overpricing