A Scenario-Based Mathematical Modeling of HIV Control in Nigeria Integrating Superinfection, Drug Resistance, and Future Vaccine Introduction

This study develops a mathematical model of HIV transmission in Nigeria to assess how scaling up antiretroviral therapy, promoting behavioral change, and managing drug resistance could shape epidemic outcomes, while also exploring the potential added impact of introducing a future HIV vaccine. The model incorporates eight interconnected compartments representing susceptible, infected with primary and secondary infections, treated individuals, drug-resistant cases, vaccinated, recovered with partial immunity, and behavioral intervention. Parameterized with epidemiological data for Nigeria, the model explores Nigerian epidemic pattern under distinct and combined control measures. Simulation results show that early and high-coverage vaccination, specifically with high-efficacy and slow waning, reduces both primary and secondary infections. ART coverage is observed to be critical in curbing the resistant strain, while behavioral reinforcement amplifies the effectiveness of biomedical interventions. However, scenarios with poor ART adherence or high superinfection potential reveal resurgence in resistant infections, emphasizing the danger posed by superinfection. Combined strategy simulations produced the most significant and sustained reductions in HIV prevalence and resistance burden. The findings in this study underscore the importance of coordinated, multi-pronged strategies for HIV control in Nigeria. The model offers a valuable policy tool for evaluating trade-offs between intervention options and guiding data-driven public health planning.