Forecasting COVID-19 infection trends and new hospital admissions in England due to SARS-CoV-2 Variant of Concern Omicron = Estimación de las tendencias de infección por COVID-19 y de nuevos ingresos hospitalarios en Espa ̃na debido a la variante Ómicron del SARS-CoV-2
Articolo
Data di Pubblicazione:
2021
Citazione:
Forecasting COVID-19 infection trends and new hospital admissions in England due to SARS-CoV-2 Variant of Concern Omicron = Estimación de las tendencias de infección por COVID-19 y de nuevos ingresos hospitalarios en Espa ̃na debido a la variante Ómicron del SARS-CoV-2 / A. Giovanni Gerli, S. Centanni, J. B Soriano, J. Ancochea. - In: ARCHIVOS DE BRONCONEUMOLOGÍA. - ISSN 0300-2896. - 58:(2021), pp. 200-202. [10.1101/2021.12.29.21268521]
Abstract:
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.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
Computational model; Epidemiological modeling; Mathematical modeling; Parameter estimation method; Predictive modeling
Elenco autori:
A. Giovanni Gerli, S. Centanni, J. B Soriano, J. Ancochea
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