Modeling the public health impact of partial vaccination and vector control strategies on malaria transmission

Malaria remains a major global public health challenge, highlighting the need for mathematical models that realistically represent the effects of vaccination and vector control. In this study, we develop an eight-compartment deterministic ordinary differential equation model incorporating partial vaccine efficacy, breakthrough infections, waning immunity, and vaccine-assisted recovery. The model is shown to be mathematically well posed through positivity, boundedness, and existence and uniqueness analyses. The basic reproduction number ( $$\mathcal {R}_0$$ ) is derived using the next-generation matrix method, and stability analysis establishes the global asymptotic stability of the disease-free equilibrium for $$\mathcal {R}_0<1$$ and the endemic equilibrium for $$\mathcal {R}_0>1$$ . Bifurcation analysis confirms a forward bifurcation at $$\mathcal {R}_0=1$$ . Global sensitivity analysis using Latin Hypercube Sampling and Partial Rank Correlation Coefficients, together with numerical simulations, identifies the key parameters influencing malaria transmission. The results show that partial vaccination reduces disease burden and delays infection peaks but is insufficient for malaria elimination when implemented alone. Combining vaccination with effective vector-control measures provides a more effective strategy for reducing transmission and achieving sustained malaria control.