Spread and seasonality of COVID-19 pandemic confirmed cases in sub-Saharan Africa: experience from Democratic Republic of Congo, Nigeria, Senegal, and Uganda

Abstract

Abstract Background The COVID-19 pandemic has impacted the world negatively with huge health and socioeconomic consequences. This study estimated the seasonality, trajectory, and projection of COVID-19 cases to understand the dynamics of the disease spread and inform response interventions. Method Descriptive analysis of daily confirmed COVID-19 cases from January 2020 to 12th March 2022 was conducted in four purposefully selected sub-Saharan African countries (Nigeria, Democratic Republic of Congo (DRC), Senegal, and Uganda). We extrapolated the COVID-19 data from (2020 to 2022) to 2023 using a trigonometric time series model. A decomposition time series method was used to examine the seasonality in the data. Results Nigeria had the highest rate of spread (β) of COVID-19 (β = 381.2) while DRC had the least rate (β = 119.4). DRC, Uganda, and Senegal had a similar pattern of COVID-19 spread from the onset through December 2020. The average doubling time in COVID-19 case count was highest in Uganda (148 days) and least in Nigeria (83 days). A seasonal variation was found in the COVID-19 data for all four countries but the timing of the cases showed some variations across countries. More cases are expected in the 1st (January-March) and 3rd (July–September) quarters of the year in Nigeria and Senegal, and in the 2nd (April-June) and 3rd (October-December) quarters in DRC and Uganda. Conclusion Our findings show a seasonality that may warrant consideration for COVID-19 periodic interventions in the peak seasons in the preparedness and response strategies.

Keywords

• COVID-19
• Trigonometric model
• Mathematical projection
• Sub-Saharan Africa