COX PROPORTIONAL HAZARDS MODELING FOR SURVIVAL ANALYSIS OF HIV/AIDS PATIENTS IN GHANA: A LONGITUDINAL BIOSTATISTICAL APPROACH

This study addresses the urgent public health challenge of HIV/AIDS in Ghana by analyzing the survival outcomes of patients using Cox Proportional Hazards Modeling. Despite expanded antiretroviral therapy (ART) coverage, Ghana still reports high AIDS-related mortality and disparities in treatment adherence and healthcare access. The research is critical for improving survival prediction and informing targeted interventions. The objective was to identify demographic, clinical, and geographic factors influencing mortality among HIV/AIDS patients from 2020 to 2024. A retrospective cohort of 6,250 patients was analyzed using multivariate Cox regression with time-dependent covariates. Major findings indicate that age (HR = 1.05), tuberculosis co-infection (HR = 2.00), and rural residence (HR = 1.60) significantly increase mortality risk, while higher ART adherence (HR = 0.95), CD4 count (HR = 0.98), and socio-economic status (HR = 0.92) are protective. The overall model fit was strong (C-index = 0.84), with significant correlation coefficients: CD4 count (r = -0.81), ART adherence (r = -0.78), socio-economic status (r = -0.74), and healthcare accessibility (r = -0.92). These results reveal a multidimensional survival landscape shaped by behavioral, biological, and structural factors. The study concludes that early diagnosis, enhanced adherence programs, and rural healthcare investments can substantially improve outcomes. It recommends the adoption of dynamic survival modeling frameworks and cross-sectoral interventions to reduce mortality and promote equity in HIV care.