Modelling and Analysis of Malaria and Ebola Co-Infection Dynamics: Insights, Implications, and Future Perspectives

Abstract

Abstract Background: Malaria and Ebola co-infection refers to the simultaneous presence of the malaria parasite (Plasmodium) and the Ebola virus within an individual's body. Methodology: This study establishes an epidemiological model employing non-linear differential equations to assess disease transmission via the reproduction number R0, stability, and sensitivity analysis. The conclusion is that the disease-free equilibrium point exists at specific values and is locally asymptotically stable when the reproduction number R0 is less than one, while globally stable under the same conditions. Results: Sensitivity analysis indicates that parameters such as 'a', 'μh', 'γD', and 'βD' have a substantial impact on the reproduction number. The simulated results highlight that increased contact between individuals infected with malaria and Ebola amplifies co-infection rates. Furthermore, increased contact between malaria-infected individuals and deceased Ebola patients, increased mosquito bite rates ('a'), and the probability of transmission from infected mosquitoes to susceptible humans ('b') all contribute to increased malaria and Ebola co-infections. Conclusion and future work: The model's capabilities include forecasting total infected cases, mortality rates, and providing information on the spread of the co-infection. Recommendations involve environmental alterations to achieve a disease-free state. Future work entails extending the model by introducing treatment or prevention compartments to address individuals with co-infections of Ebola and malaria. This research significantly contributes to understanding co-infection dynamics, emphasising the need for strategic measures to mitigate the spread and impact of malaria and Ebola co-infections.