MATLAB Implementation of SIS Epidemic Model

The following MATLAB code implements the SIS (Susceptible-Infected-Susceptible) epidemic model. This compartmental model utilizes ordinary differential equations to simulate disease transmission and recovery dynamics within a population. The model tracks two distinct states: susceptible individuals and infected individuals, with transmission rate (β) and recovery rate (γ) serving as critical parameters governing system behavior. The implementation is structured into four key sections: parameter initialization, initial condition setup, numerical integration using MATLAB's ODE solver, and result visualization. The core algorithm employs ode45 function to solve the coupled differential equations: dS/dt = -βSI + γI and dI/dt = βSI - γI, where S and I represent susceptible and infected population fractions respectively. Key implementation features include: - Parameter validation and range checking - Time-step adaptive numerical integration - Real-time trajectory plotting of population dynamics - Infection peak detection and basic reproduction number (R₀) calculation This model serves as an essential tool for understanding disease transmission mechanisms, evaluating intervention strategies, and predicting epidemic trends through parameter sensitivity analysis.