Mathematical Modeling of Malaria-Tuberculosis Co-Infection

Malaria and tuberculosis co-infection represents a critical and growing public health concern, particularly in regions where both diseases are highly endemic and health systems face significant constraints. The dual burden of these infections not only increases morbidity and mortality but also complicates diagnosis, treatment, and control efforts. This study develops a comprehensive mathematical model to investigate the transmission dynamics of malaria-tuberculosis co-infection within a human population, with a strong emphasis on its public health implications. The model is systematically decomposed into disease-specific sub-models to enable rigorous theoretical analysis of both individual and combined disease dynamics. A key finding is the occurrence of backward bifurcation in the co-infection system, indicating that reducing the basic reproduction number () below unity is not sufficient for disease elimination. This result has important public health implications, as it suggests that standard control targets may be inadequate in co-endemic settings. Sensitivity analysis identifies critical parameters influencing disease spread, including transmission rates, treatment efficacy, and co-infection progression rates. These findings provide actionable insights for policymakers by highlighting priority areas for intervention. The results underscore the need for integrated and coordinated control strategies that simultaneously address malaria and tuberculosis, rather than treating them as independent diseases.