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Nigerian COVID-19 Incidence Modeling and Forecasting with Univariate Time Series Model

Taiwo, Abass and Adedotun, Adedayo F. and Olatayo, T. O. (2022) Nigerian COVID-19 Incidence Modeling and Forecasting with Univariate Time Series Model. In: Decision Sciences for COVID-19. Sprintger, pp. 137-150. ISBN 978-3-030-87018-8, ISBN 978-3-030-87019-5 (eBook)

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The occurrence of COVID-19 has given rise to dreadful medical difficulties due to its hyper-endemic effects on the human population. This made it fundamental to model and forecast COVID-19 pervasiveness and mortality to control the spread viably. The COVID-19 data used was from February, 28, 2020 to March 1, 2021. ARIMA(1,2,0) was selected for modeling COVID-19 confirmed and ARIMA (1,1,0) for death cases. The model was shown to be adequate for modeling and forecasting Nigerian COVID-19 data based on the ARIMA model building results. The forecasted values from the two models indicated Nigerian COVID-19 cumulative confirmed and death case continues to rise and maybe in-between 189,019–327,426 and interval 406–3043, respectively in the next 3 months (May 30, 2021). The ARIMA models forecast indicated an alarming rise in Nigerian COVID-19 confirmed and death cases on a daily basis. The findings indicated that effective treatment strategies must be put in place, the health sector should be monitored and properly funded. All the protocols and restrictions put in place by the NCDC, Nigeria should be clung to diminish the spread of the pandemic and possible mortality before immunizations that can forestall the infection is developed.

Item Type: Book Section
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Engineering, Science and Mathematics > School of Mathematics
Depositing User: nwokealisi
Date Deposited: 10 Nov 2023 16:57
Last Modified: 10 Nov 2023 16:57

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