Time Series Analysis of Malaria Cases at Redeemer's University Health Centre (2014–2022)

Planning for public health effectively requires an awareness of the temporal dynamics of malaria, which continues to be a major worldwide health concern. The study aimed at analysing the trend of malaria cases by investigating the factors associated with these cases, also to forecast future occurrences in Redeemer’s University. The time series data was modelled using the Autoregressive Integrated Moving Average (ARIMA) approach. The parameters for the ARIMA model were selected through the Box-Jenkins method, a systematic technique for identifying the optimal model parameters. Analysis showed a seasonal pattern in malaria cases, rainfall emerged as the most important factor with a strong statistical association indicating that higher rainfall levels lead to increased malaria incidence. The dry season also significantly influenced malaria cases, although its impact was less pronounced compared to rainfall. The result of this study predicted that there will be a downward trend of malaria cases in Redeemer’s University for the next five years (2023 – 2027). This study recommended that Redeemer’s University should provide more preventive measures and effective intervention strategies such as vaccines, mosquito nets, insecticides to control malaria fever.