Abstract:
The primary goal of this research was to forecast Kenya’s daily COVID-19 case count using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. SARIMA is a time series forecasting technique that combines seasonal, moving average, autoregressive, and differencing components to capture intricate temporal patterns. This study aimed to forecast future case counts, assess seasonal variations, and evaluate efficacy of mitigation measures by utilizing historical COVID-19 incidence data from Kenya. The study shows how well SARIMA captures and predicts epidemic dynamics through rigorous model evaluation and validation against real-world data. Results aid in improving epidemiological surveillance and providing guidance for decision-making regarding Kenya’s COVID-19 pandemic response.
