Leveraging Multi-Component Control Strategies for Marburg Virus Suppression: A Mathematical Modeling Approach

Abstract

Marburg virus disease is a severe and often fatal hemorrhagic fever that poses a significant threat to global health. Its high transmissibility, incubation period, and nonspecific symptoms hinder early detection and effective containment. Limited public awareness, delayed diagnosis, and restricted access to reliable health information further heighten the risk of widespread outbreaks.

This study develops a mathematical model for Marburg virus transmission using a compartmental SEIR (Susceptible, Exposed, Infectious, Recovered) framework. The inclusion of an Exposed compartment captures the latent period before symptom onset, improving the accuracy of disease progression modeling. Key parameters, such as the basic reproduction number ​, are estimated to evaluate the virus's potential for sustained transmission. Sensitivity and stability analyses identify the most critical factors influencing outbreak dynamics and thresholds for containment.

To guide intervention efforts, optimal control strategies such as public education, early diagnosis and treatment, case isolation, and vector control are incorporated into the model. Numerical simulations and cost-effectiveness assessments demonstrate that combined strategies can reduce infection rates and lower ​ below the epidemic threshold.

Despite data limitations and implementation challenges, this model offers valuable insights for public health decision-making, emphasizing the need for integrated and timely responses to prevent future Marburg virus outbreaks.