  Non-pharmaceutical interventions (NPIs) are effective measures to contain a
pandemic. Yet, such control measures commonly have a negative effect on the
economy. Here, we propose a macro-level approach to support resolving this
Health-Economy Dilemma (HED). First, an extension to the well-known SEIR model
is suggested which includes an economy model. Second, a bi-objective
optimization problem is defined to study optimal control policies in view of
the HED problem. Next, several multi-objective evolutionary algorithms are
applied to perform a study on the health-economy performance trade-offs that
are inherent to the obtained optimal policies. Finally, the results from the
applied algorithms are compared to select a preferred algorithm for future
studies. As expected, for the proposed models and strategies, a clear conflict
between the health and economy performances is found. Furthermore, the results
suggest that the guided usage of NPIs is preferable as compared to refraining
from employing such strategies at all. This study contributes to pandemic
modeling and simulation by providing a novel concept that elaborates on
integrating economic aspects while exploring the optimal moment to enable NPIs.
