A comparative study of simulation-based inference methods for epidemic models with identifiability considerations (opens in new tab)

Author summary We developed a systematic framework to compare methods for estimating parameters in epidemic models. These models help researchers understand how diseases spread and how interventions may change the course of an outbreak. However, estimating model parameters can be difficult because traditional likelihood-based methods are often impractical for realistic epidemic models. Simulation-based inference offers an alternative by generating synthetic epidemic trajectories and comparing...