COVID-19 prevalence estimation: Four most affected African countries

Area of Science:

• Epidemiology
• Public Health
• Time Series Analysis

Background:

• Global disease outbreaks, including the COVID-19 pandemic, pose significant public health threats.
• African nations like South Africa, Egypt, Nigeria, and Ghana are heavily impacted, necessitating localized monitoring and prediction.
• Existing statistical models, such as linear regression and ARIMA, have been used for disease prediction.

Purpose of the Study:

• To forecast the prevalence trends of COVID-19 in key African countries.
• To evaluate the suitability of Autoregressive Integrated Moving Average (ARIMA) models for predicting COVID-19.
• To inform public health strategies for pandemic control in Africa.

Main Methods:

• Utilized ARIMA models to forecast COVID-19 prevalence trends in South Africa, Egypt, Nigeria, and Ghana.
• Employed time series data from February 21, 2020, to June 16, 2020, sourced from the World Health Organization.
• Selected optimal ARIMA models based on minimum Akaike Information Criterion correction (AICc) and statistically significant parameters.

Main Results:

• Identified specific ARIMA models as best fits for each country: ARIMA (0,2,3) for South Africa, ARIMA (0,1,1) for Nigeria, ARIMA (3,1,0) for Ghana, and ARIMA (0,1,2) for Egypt.
• Forecasting indicated an exponential growth trend for COVID-19 in Africa.
• Confirmed the appropriateness of ARIMA models for predicting COVID-19 prevalence.

Conclusions:

• ARIMA models are effective for forecasting COVID-19 trends in African countries.
• The projected exponential growth necessitates immediate attention from governments and health authorities.
• Proactive measures and strategic planning are crucial to mitigate the impact of the pandemic in Africa.