Modeling HBV transmission dynamics in Indonesia (2024–2030) using a SIVRM model: Evaluating optimal control strategies for elimination by 2030

Hepatitis B remains a global health concern. Achieving the World Health Organization's (WHO) goal of eliminating the disease by 2030 requires a comprehensive understanding of its transmission dynamics. This study aimed to develop and apply an extended SIVRM (Susceptible-Infected-Vaccinated-Recovered-Mortality) model to simulate hepatitis B transmission in Indonesia and to evaluate optimal vaccination strategies. The model comprises 14 compartments that distinguish between vertical and horizontal transmission, account for vaccination and loss of immunity, and incorporate hepatitis B virus (HBV) reactivation among recovered individuals, a novel feature of this model. Parameters were estimated using data from the Social Security Administrator for Health (BPJS Kesehatan) from 2019 to 2023 through a least-squares fitting approach. The basic reproduction number ([Formula: see text]) and disease-free equilibrium (DFE) were analytically derived. Simulations were conducted using MATLAB 2018 to project hepatitis B trends from 2024 to 2030 and to evaluate scenarios of adult and newborn vaccination coverage. A key finding from the parameter estimation was an HBV reactivation rate of 0.30, indicating that 30% of recovered individuals remain at risk. The model estimated a baseline [Formula: see text] of 4.39, indicating that current control strategies in Indonesia are insufficient to achieve the WHO elimination goal. However, scenario-based analysis revealed that increasing adult vaccination coverage to at least 59%, while maintaining newborn vaccination at 70%, could reduce [Formula: see text] to 0.90 and substantially lower the disease burden. These findings underscore the urgent need to expand adult vaccination programs and strengthen post-recovery monitoring to advance hepatitis B elimination in Indonesia.