Mathematical Modeling of Typhoid Fever Transmission Dynamics: A Sensitivity Analysis and Implications for Public Health Strategies - Hassan Muhammad; Auwal Abdullahi (Mikailalsys Journal of Advanced Engineering International, 2026)
Typhoid fever remains an important public health concern, requiring robust analytical approaches to understand its transmission dynamics and support effective prevention and control strategies. This study develops a comprehensive mathematical model of typhoid fever transmission to examine the interactions among factors influencing disease spread and to provide evidence for improved control and eradication strategies. The model incorporates population replenishment through births and was validated using existing data to assess its ability to represent disease dynamics. Mathematical analysis was conducted to determine equilibrium states and the basic reproduction number, (R0), while sensitivity analysis was performed to identify parameters with substantial influence on typhoid transmission. Numerical solutions were obtained using the fourth-order Runge–Kutta method over a 40-year simulation period and implemented in MATLAB. The findings show that (R0) is a critical threshold governing the dynamics of typhoid fever. When (R0<1), the disease-free equilibrium is locally stable, indicating that disease transmission will eventually decline; conversely, when (R0>1), an endemic equilibrium exists, indicating the persistence of the disease within the population. Sensitivity analysis further demonstrates the relative influence of model parameters on disease transmission, providing insights into factors that may be prioritized in control interventions. These findings demonstrate the utility of mathematical modeling for understanding typhoid fever transmission and evaluating disease-control strategies. The study contributes a quantitative framework that can support policymakers and healthcare professionals in designing evidence-based interventions aimed at reducing typhoid transmission, strengthening prevention efforts, and improving public health outcomes.