The drive-through model developed in this study is a meta-model (or models of models) that as described by Obsie et al. [33], represents a deterministic proxy for stochastic simulation models. However, developing this type of meta-models requires running complex simulation for many combinations and then using the data generated by each run to create a simpler machine learning model that is a reasonable approximation of the initial simulation model. The meta-models can then provide quick predictions for different input values. While simulation-based or meta-modeling is not a new concept [34], its application in different fields and simulation types are still limited. In this study, we applied meta-modeling approach in the context of mass vaccination.