Non-linearity in epidemiology refers to situations where changes in input do not produce proportional changes in output. This can occur due to a variety of factors such as heterogeneous mixing patterns among individuals, varying susceptibility to disease, and seasonality effects. Non-linear models can better capture the complexities of disease transmission and progression.
