Predicting South Africa’s Daily COVID-19 Cases using ARIMA Forecasting Model: 6 March to 6 July 2020

Abstract Background and Objective : The COVID-19 pandemic caused approximately 11,421,822 laboratory confirmed cases globally with 196,750 confirmed cases in South Africa by the 6 th of July 2020. Coronavirus is transmitted from one person to another even before any symptoms appear, thus posing a severe threat to the society as a whole. This study is aimed at coming up with an ARIMA model to predict daily COVID-19 disease cases in South Africa using data from online sources. Materials and Methods : The study used online data on daily COVID-19 reported cases in South Africa (SA) recorded from 6 March 2020 to the 6 th of July 2020. Time series analysis is used to investigate the trend in the daily COVID-19 disease cases leading to the Auto-Regressive Integrated Moving Average (ARIMA) model. Results : The time plot of the series suggests the need for differencing of the data up to the second-order to achieve a stationary time series. The best candidate model was an ARIMA(7,2,0). Residuals for the selected model are non-correlated and normally distributed with mean zero with a constant variance as expected in a good model. The fitted model predicted a continuous increase in the daily COVID-19 disease cases for the next 20 days ahead to day 143 with slight falls at a few time points. Conclusion : The results showed that ARIMA models can be applied to COVID-19 patterns in South Afriva. The model forecasted a continuous increase in the daily COVID-19 cases in South Africa. These results are important for public health planning in order combat the pandemic.