Deterministic Modeling of HIV–Malaria Co-Infection and Sensitivity Analysis in Papua

Abstract

HIV and malaria co-infection poses a significant public health challenge in Papua, Indonesia, where high HIV prevalence overlaps with persistent malaria endemicity. Their biological interaction worsens clinical outcomes and complicates transmission. This study develops a deterministic mathematical model using nonlinear differential equations to describe HIV--malaria co-infection dynamics, tailored to Papua's epidemiology. The model includes coupled human and vector compartments and is analyzed through disease-free and endemic equilibria. The basic reproduction number $R_0$ is derived using the next-generation matrix method and its sensitivity is assessed using normalized forward sensitivity indices to identify key parameters affecting transmission. The results show that the HIV transmission rate ($\beta_H$), the mosquito bite rate ($b_M$), and the malaria transmission from humans to mosquitoes ($\beta_V$) increase the most strongly $R_0$, while the progression of HIV to AIDS ($\alpha_1$), malaria-induced mortality ($\delta_M$), and vector mortality ($\mu_V$) reduce it. Numerical simulations based on realistic initial conditions for Papua indicate that the system reaches a stable equilibrium when interventions target the most sensitive parameters. These findings provide a mathematical foundation for integrated control strategies, emphasizing reduced human--vector contact, suppression of HIV transmission, and effective vector control. The model enriches biomathematics research on co-infection dynamics and supports evidence-based policymaking for managing dual epidemics in regions like Papua.