Forecasting COVID-19 Chile' second outbreak by a generalized SIR model with constant time delays and a fitted positivity rate.
Math Comput Simul
; 193: 1-18, 2022 Mar.
Article
em En
| MEDLINE
| ID: mdl-34608351
The COVID-19 disease has forced countries to make a considerable collaborative effort between scientists and governments to provide indicators to suitable follow-up the pandemic's consequences. Mathematical modeling plays a crucial role in quantifying indicators describing diverse aspects of the pandemic. Consequently, this work aims to develop a clear, efficient, and reproducible methodology for parameter optimization, whose implementation is illustrated using data from three representative regions from Chile and a suitable generalized SIR model together with a fitted positivity rate. Our results reproduce the general trend of the infected's curve, distinguishing the reported and real cases. Finally, our methodology is robust, and it allows us to forecast a second outbreak of COVID-19 and the infection fatality rate of COVID-19 qualitatively according to the reported dead cases.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
País/Região como assunto:
America do sul
/
Chile
Idioma:
En
Revista:
Math Comput Simul
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Chile
País de publicação:
Holanda