Traditional epidemiological models, such as SIR models, are often based on differential equations and assume a homogeneous mixing of the population. However, real-world populations are heterogeneous and exhibit complex interaction patterns. ABMs can capture this heterogeneity by modeling individuals with varying characteristics, such as age, health status, and social behavior, which can significantly influence disease dynamics.
