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ABSTRACT
The use of matrices in epidemiology provides a practical and flexible way to study how diseases spread, measure the impact of control measures, and predict the course of an outbreak. By arranging data into rows and columns, matrices present complex relationships between different population groups and the stages of disease progression in a clear and organized form. In disease modeling, they are often combined with compartmental models such as the SIR (Susceptible–Infectious–Recovered) framework to trace how individuals move between health states over time. Transition matrices can be adjusted to reflect differences in age, location, or patterns of contact, making them adaptable to many real-world situations. Matrix methods also make it possible to calculate the basic reproduction number (Ro), test the stability of a disease free state, and assess how effective certain interventions may be. By blending mathematical precision with public health goals, matrix based approaches help researchers understand epidemics better and guide practical strategies for preventing and controlling disease.
KEYWORDS: Susceptible,Infected, Recovered, Matrices, Disease Progression, Epidemics.
