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The ongoing COVID-19 pandemic highlights the essential role of mathematicalmodels in understanding the spread of the virus along with a quantifiable andscience-based prediction of the impact of various mitigation measures. Numeroustypes of models have been employed with various levels of success. This leadsto the question of what kind of a mathematical model is most appropriate for agiven situation. We consider two widely used types of models: equation-basedmodels (such as standard compartmental epidemiological models) and agent-basedmodels. We assess their performance by modeling the spread of COVID-19 on theHawaiian island of Oahu under different scenarios. We show that when it comesto information crucial to decision making, both models produce very similarresults. At the same time, the two types of models exhibit very differentcharacteristics when considering their computational and conceptual complexity.Consequently, we conclude that choosing the model should be mostly guided byavailable computational and human resources.

A study of computational and conceptual complexities of compartment and agent based models