Modélisation et prévision du nombre d’infections au coronavirus au Togo: une approche par un modèle ARIMA avec le logiciel R

Modeling and forecasting the number of coronavirus infections in Togo: an ARIMA model approach with R software

Mayo Takémsi Norris Kadanga and Fo-Kossi Edem Togbenu

MPRA Paper from University Library of Munich, Germany

Abstract: In this paper, we attempt to propose a short-term prediction model of the number of new cases of coronavirus infections in Togo using the R software. From the original daily data, a new weekly database containing 80 observations was constructed. After splitting this new database into training and test samples in order to select the appropriate model, the database was then used to build our forecasting model, the ARIMA(2,1,2) model. This model was used to make forecasts for the next four weeks. The findings show that Togo can expect approximately 1200 infections in average every week if suitable measures are not adopted in order to stop the rapid spread of the virus in the country.

Keywords: Coronavirus; COVID-19; Forecast; ARIMA (search for similar items in EconPapers)
JEL-codes: C53 (search for similar items in EconPapers)
Date: 2021-09-24
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https://mpra.ub.uni-muenchen.de/109893/1/MPRA_paper_109893.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/109929/1/MPRA_paper_109929.pdf revised version (application/pdf)
https://mpra.ub.uni-muenchen.de/110535/1/MPRA_paper_110535.pdf revised version (application/pdf)

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