Muhafzan
Department of Mathematics and Data Science, Universitas Andalas, Padang 25163, Indonesia
Lyra Yulianti
Department of Mathematics and Data Science, Universitas Andalas, Padang 25163, Indonesia
Robi Maulana Butar-Butar
Department of Mathematics and Data Science, Universitas Andalas, Padang 25163, Indonesia
Wan Zuki Azman Wan Muhamad
Department of Mathematical Sciences, Faculty of Intelligent Computing, Universiti Malaysia Perlis (UniMAP), 02600 Arau, Perlis, Malaysia
This paper proposes a deterministic compartmental epidemic model incorporating three infected classes to capture multistage disease progression and heterogeneous infectiousness. The model explicitly accounts for neonatal vaccination by introducing a fraction of newborns immunized at birth, thereby reducing the inflow into the susceptible population. Using the next-generation matrix approach, an explicit expression for the basic reproduction number is derived. Rigorous qualitative analysis is conducted to establish the existence, positivity, boundedness, and local stability of both disease-free and endemic fixed points. It is shown that the disease-free fixed point is locally asymptotically stable when , whereas a positive endemic fixed point exists and becomes locally asymptotically stable when Numerical simulations are performed to support the theoretical results and to explore the epidemiological impact of neonatal vaccination. The results indicate that increasing vaccination coverage significantly reduces infection prevalence, suppresses epidemic peaks, and enhances convergence toward the fixed point, even when endemicity persists. These findings highlight the critical role of early-life immunization as an effective public health strategy for controlling multistage infectious diseases and mitigating long-term epidemic burden.