1. Discrete Gompertz and Generalized Logistic models for early monitoring of the COVID-19 pandemic in Cuba.
- Author
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Pérez Maldonado, María Teresa, Bravo Castillero, Julián, Mansilla, Ricardo, and Caballero Pérez, Rogelio Óscar
- Subjects
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COVID-19 pandemic , *DIFFERENCE equations , *COMMUNICABLE diseases , *DIFFERENTIAL equations , *PANDEMICS , *EPIDEMICS , *COVID-19 - Abstract
The COVID-19 pandemic has motivated a resurgence in the use of phenomenological growth models for predicting the early dynamics of infectious diseases. These models assume that time is a continuous variable, whereas in the present contribution the discrete versions of Gompertz and Generalized Logistic models are used for early monitoring and short-term forecasting of the spread of an epidemic in a region. The time)continuous models are represented mathematically by first-order differential equations, while their discrete versions are represented by first-order difference equations that involve parameters that should be estimated prior to forecasting. The methodology for estimating such parameters is described in detail. Real data of COVID)19 infection in Cuba is used to illustrate this methodology. The proposed methodology was implemented for the first thirty-five days and was used to predict accurately the data reported for the following twenty days. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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