Optimal Control and Stability Analysis in Disease Transmission Models

Abstract

This study explains how mathematical models help understand and control the spread of infectious diseases. Through using optimal control and stability analysis, researchers can find how diseases grow, how fast they spread, and what measures can stop them. Models like SEIR, SVIR, and SEIQR help study diseases such as measles, malaria, dengue, and tuberculosis. These models show that factors like vaccination, human behavior, and population movement affect transmission. Stability and control analysis help identify safe conditions where diseases stop spreading. This research helps design better strategies for disease prevention and long-term public health planning.