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

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dc.creatorTaiwo, Abass, Adedotun, Adedayo F., Olatayo, T. O.
dc.date2022
dc.date.accessioned2025-04-15T11:13:12Z
dc.descriptionThe 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.
dc.formatapplication/pdf
dc.identifierhttp://eprints.covenantuniversity.edu.ng/17578/
dc.identifier.urihttps://repository.covenantuniversity.edu.ng/handle/123456789/48298
dc.languageen
dc.publisherSprintger
dc.subjectQA Mathematics
dc.titleNigerian COVID-19 Incidence Modeling and Forecasting with Univariate Time Series Model
dc.typeBook Section

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