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Time Series Analysis in COVID-19 Daily Reported Cases in South Africa: A Box-Jenkins Methodology

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Intelligent Computing and Optimization (ICO 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 854))

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Abstract

COVID-19 has affected the lives of South Africans and the world at large. In this study, daily COVID-19-reported cases are considered. The COVID-19 pandemic has affected healthcare facilities and all other economic structures in South Africa. Forecasting daily COVID-19 Cases is helpful and reduces the pressure of uncertainty this pandemic has and the understanding of its nature. In this study, ARIMA and SARIMA models are used to understand the nature and patterns of the COVID-19 pandemic The R Software is used in the analysis and the models are selected using the AIC and BIC criteria by observing the ACF and PACF of each of the models. This study proposes that forecasting can help the South African government and healthcare officials to understand the nature of COVID-19 and observe its effects on the economy. The Box-Jenkins methodology is applied using R Software so to choose the right model and forecast for the next 60 days. We hope decisions that will be made will help manage and control the COVID-19 pandemic.

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Abbreviations

AIC:

Akaike’s Information Criterion

BIC:

Bayesian Information Criterion

COVID-19:

Coronavirus disease 2019

AR:

Autoregressive

MA:

Moving Average

ARMA:

Autoregressive Moving Average

ARIMA:

Autoregressive Integrated Moving Average

SARIMA:

Seasonal Autoregressive Integrated Moving Average

D/d:

Differencing

ACF:

Autocorrelated Function

PACF:

Partial Autocorrelated Function

NAAT:

Nucleic Acid Amplification Test

NNAR:

Neural network Nonlinear AutoRegressive (NNAR)

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Correspondence to Elias Munapo .

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Motene, H., Seaketso, P., Munapo, E., Mdlongwa, P. (2023). Time Series Analysis in COVID-19 Daily Reported Cases in South Africa: A Box-Jenkins Methodology. In: Vasant, P., et al. Intelligent Computing and Optimization. ICO 2023. Lecture Notes in Networks and Systems, vol 854. Springer, Cham. https://doi.org/10.1007/978-3-031-50151-7_1

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