Incorporating random effects into epidemiological models can be complex. One challenge is the computational difficulty, as models with random effects often require sophisticated algorithms and greater computational power. Another issue is the potential for overfitting, where the model becomes too tailored to the sample data and loses its predictive power for other populations.
