Abstract
This study develops and analyzes a compartmental SEICRV model to investigate the transmission dynamics of meningitis. The model incorporates key parameters such as vaccination, recovery, and treatment rate. Using meningitis incidence data from the Institute for Health Metrics and Evaluation, we calibrate the model through least-squares fitting to estimate parameters governing disease progression, recovery, and intervention impact. The basic reproduction number, R0, is derived to assess the potential for disease spread, and sensitivity analysis is conducted to determine the parameters with the most significant influence on R0. The scenario analysis explore the effects of varying vaccination rates, treatment coverage, and vaccine effectiveness. The results demonstrate that higher vaccination coverage and effective treatment reduce the peak size of infectious and carrier populations and delay outbreak peaks. This model provides a valuable tool for assessing meningitis control measures and supports evidence-based decision-making in regions with a high meningitis burden, highlighting the importance of targeted interventions to reduce disease transmission and improve population health outcomes.