Modeling and analysis of microbial dynamics in malaria and measles co-infections with public awareness interventions via numerical simulation

Malaria and measles continue to be a burning world health issue, especially in areas where medical facilities are underdeveloped and where the disease burden is high. Along with measles, a highly contagious respiratory virus belonging to the genus Morbillivirus, malaria caused by the protozoan parasite Plasmodium (carried by the Anopheles mosquito) is linked to significant morbidity and mortality on the global level. This is further increased by the fact that they co-exist in human populations and consequently, their co-infection relationship is an important field of research. This study uses a mathematical modeling fractional-order model that explores the microbial dynamics of malaria and measles co-infections, explicitly factoring in the public awareness (enlightenment) interventions as a control measure to reduce the spread. This model is built to have compartmental structures that consider the susceptible and infected as well as recovered groups in addition to incorporating the impact of behavioral change brought about by awareness. The Caputo-Fabrizio fractional derivative is used to obtain the inherent memory and hereditary effects in the processes of spreading and treating the disease. This fractional framework is more realistic and precise in the behavior of diseases in comparison to conventional integer-order models. To investigate the qualitative behavior of the system and to determine how sensitive the results of co-infection are to the most important parameters, stability analysis and numerical simulations are performed. Findings indicate that disease prevalence and epidemic thresholds are significantly lowered, and the severity of malaria-measles co-infections is restricted by awareness interventions. In addition, the fractional-order methodology improves the accuracy of the model, capturing the longevity of the dynamics of the infection and the long-term effectiveness of interventions. The results point at the significance of the combination of medical treatment and the public awareness campaigns in the attainment of efficient disease control. Altogether, the present research adds to the body of infectious disease modeling by suggesting the importance of the use of fractional calculus to simulate co-infections and offering some strategies that can help decrease the burden of malaria and measles in vulnerable populations. • A fractional-order co-infection model for malaria and measles is developed using the Caputo–Fabrizio derivative. • The model integrates public awareness interventions to capture behavioral effects on disease spread. • Fractional calculus provides realistic memory and hereditary effects in infection and recovery dynamics. • Stability and sensitivity analyses reveal key parameters influencing malaria–measles co-infection outcomes. • Public awareness campaigns combined with medical treatment significantly reduce disease burden and epidemic thresholds.