GS4 Student Scholars Symposium

Forecasting is essential for predicting trends and supporting public health decisions. This study applies the Auto-Regressive Integrated Moving Average (ARIMA) model to analyze and forecast Human Immunodeficiency Virus (HIV) prevalence using monthly data (2010–2021) from Jibril Mai-Gwari I Memorial Hospital, Birnin Gwari, Nigeria. Among eight models, ARIMA(0,1,2)(0,0,1)₁₂ was the best fit based on the Akaike Information Criterion (AIC), Mean Squared Error (MSE), and Log-Likelihood. Residual diagnostics confirmed model adequacy, with normally distributed residuals (Shapiro-Wilk test, p = 0.5239) and no significant autocorrelations (Ljung-Box test). The forecast suggests a decline in HIV prevalence, highlighting ARIMA's effectiveness in capturing epidemiological trends and informing public health interventions. This study is conducted in collaboration with Dr. Okeniyi, O.M., Department of Statistics, Federal Polytechnic Offa, Kwara State, Nigeria.