COVID-19 Forecasts for Cuba Using Logistic Regression and Gompertz Curves.
MEDICC Rev
; 22(3): 32-39, 2020 Jul.
Article
em En
| MEDLINE
| ID: mdl-32812897
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.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Pneumonia Viral
/
Modelos Logísticos
/
Infecções por Coronavirus
/
Previsões
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
País/Região como assunto:
Caribe
/
Cuba
/
Europa
Idioma:
En
Revista:
MEDICC Rev
Assunto da revista:
SAUDE PUBLICA
Ano de publicação:
2020
Tipo de documento:
Article
País de publicação:
Estados Unidos