Modeling the Impacts of Vaccination and other Interventions on Malaria Transmission Dynamics

Malaria remains a persistent global health challenge, with its burden concentrated in Sub-Saharan Africa and other endemic regions where transmission is sustained by interactions between human and mosquito populations. Despite progress in prevention and treatment, the emergence of partial immunity, asymptomatic carriers, and insecticide resistance complicates control efforts. In this study, we formulate and analyze a nonlinear compartmental model that incorporates a vaccination class alongside traditional malaria interventions. The model’s mathematical properties are established by proving the positivity and boundedness of solutions, and by deriving the disease-free and endemic equilibria. Using the Diekmann-Heesterbeek-Metz Next Generation Matrix approach, we obtain the effective reproduction number and conduct rigorous local and global stability analyses of both equilibria. Furthermore, local sensitivity analysis is performed to identify key parameters driving transmission, highlighting the roles of vaccine uptake, waning immunity, mosquito–human contact rate, and vaccine efficacy. Numerical simulations illustrate the epidemiological impact of vaccination, showing that increased vaccine coverage substantially reduces infection prevalence and sustains lower transmission levels. To complement this, we extend the analysis with a cost-effectiveness evaluation of three optimal control strategies combining insecticide-treated nets, diagnostic surveillance, and environmental sanitation. The results show that while single or dual interventions moderately reduce infections, the integrated triple-intervention strategy together with the vaccinated compartment achieves the greatest epidemiological impact while also being the most cost-effective, yielding the lowest ACER and a negative ICER, indicating cost savings. These findings emphasize that vaccination, when combined with other interventions, not only reduces malaria burden but also represents an economically justified approach to sustainable control.