Eigenvectors are crucial in Epidemiology because they can help model the spread of infectious diseases. Specifically, they are used in analyzing the compartmental models like the SIR (Susceptible, Infected, Recovered) model. These models are represented by matrices that describe the rate of transition between different states of the population. Eigenvectors help identify the dominant patterns in these transitions, which can be used to predict the future course of an outbreak.
