Sensitivity Model Analysis of a Lassa Fever Treatment Control
Achugamonu, Pius Chukwuma1 , Awah, Uchenna Chinyelugo 2, Uwakwe, Joy3, Anyanwu, Eric Onyebuchi4, Chinaka, Augustina Ifeoma 5.
1Department of Mathematics / Alvan Ikoku Federal University of Education Owerri, Imo State.
Abstract:
Lassa virus, the causative agent of Lassa fever, is listed among potential bio‑weapons agents. In recent years, cases have been imported into Germany, the Netherlands, the United Kingdom, and the United States due to the rapid expansion of international travel. Understanding its transmission dynamics is therefore of global importance. In this study, a treatment model consisting of seven mutually exclusive compartments related to Lassa fever infection was developed and analyzed. The basic reproduction number was derived, and four major research objectives were achieved. Published articles in standard journals, clinical data, and medical interviews formed the foundation of the study. The disease dynamics were fully determined by the effective reproduction number, obtained using the next‑generation matrix approach.
A deterministic compartmental model with seven epidemiological classes was formulated to describe Lassa fever transmission under treatment intervention. The effective reproduction number was computed using the next‑generation approach. Sensitivity analysis was performed to determine the relative importance of model parameters on disease transmission. Stability and sensitivity assessments employed mathematical tools such as Lyapunov functionals and the Comparison Theorem. Numerical simulations were conducted using MATLAB and MAPLE to validate and support the theoretical findings.
Sensitivity analysis revealed that the effective reproduction number is strongly influenced by specific model parameters. The treatment rate emerged as the most sensitive parameter, indicating that improvements in treatment effectiveness significantly reduce disease transmission. This was followed by the human recovery rate and then person‑to‑person contact rate. The results suggest that treatment interventions and improved recovery mechanisms have the greatest potential impact on reducing Lassa fever spread. Numerical simulations aligned with the analytical results, confirming the robustness of the model.
This study demonstrates that treatment plays a critical role in controlling Lassa fever transmission. The sensitivity analysis shows that the treatment rate is the most influential parameter, followed by human recovery rate and person‑to‑person contact. These findings indicate that control strategies should prioritize effective therapeutic interventions and public health education aimed at reducing direct human‑to‑human transmission. The model provides a useful framework for designing cost‑effective intervention strategies and guiding national Lassa fever control programs.
Key Word: Lassa fever; Lassa virus; treatment model; effective reproduction number; sensitivity analysis; mathematical epidemiology; stability analysis; disease transmission dynamics.
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