TIME SERIES ANALYSIS ON PREVALENCE OF HIV/AIDS BASED ON GENDER (A CASE OF STUDY OF BORNO STATE SPECIALIST HOSPITAL FROM (2018 – 2024)

This study examines the prevalence of HIV/AIDS as it affects gender in Borno State Specialist Hospital, Maiduguri, using time series analysis for the period 2018–2024. Secondary data obtained from hospital medical records were analyzed to identify trends, gender disparities, and future patterns in HIV/AIDS prevalence. Descriptive statistics, trend analysis, the Augmented Dickey–Fuller (ADF) stationarity test, ARIMA modeling, and an independent samples t-test were employed. The results showed that female prevalence cases were consistently higher than male cases across all years, with females recording a higher mean (444.43) compared to males (253.43). Trend analysis revealed fluctuations in both genders, with a significant spike in 2021 followed by sharp declines in 2022 and 2024. The ADF test indicated that both male and female series were non-stationary, justifying the need for differencing in time series modeling. ARIMA (0,2,1) models were fitted for each gender, though predictive accuracy was limited by the small dataset. Forecasts for 2025–2027 suggested a continued decline in HIV/AIDS prevalence for both males and females. The t-test showed no statistically significant difference between male and female mean prevalence despite numerical differences. Overall, the study concludes that HIV/AIDS prevalence is declining but gender disparities persist, emphasizing the need for sustained gender-sensitive interventions, improved healthcare access, and strengthened data systems. Recommendations include intensified awareness campaigns, enhanced healthcare infrastructure, and further research incorporating larger datasets and advanced modeling techniques.