Can synthetic controls improve causal inference in interrupted time series evaluations of public health interventions?

Advances in synthetic control methods bring new opportunities to conduct rigorous research in evaluating public health interventions. However, incorporating synthetic controls in interrupted time series studies may not always nullify important threats to validity nor improve causal inference.