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For example, a model can mechanistically represent movement and contact rates of individuals. Models for understanding are aimed at exploring how different components of a system interact to shape observed behavior of real systems. This is an important logical prediction that helped to make key decisions, but it does not, and cannot, say anything about how effective interventions like social distancing are in reducing R 0. For example, at the onset of the Covid-19 pandemic simple mathematical models were used to demonstrate how lowering the basic reproduction value, R 0, would lead to “flattening the curve” of infections over time. Models for demonstration are designed to explore ideas, demonstrate the consequences of certain assumptions, and thereby help communicate key concepts and mechanisms. Given these different purposes, models also reflect different scopes. Model purposes fall into three main categories: demonstration, understanding, and prediction.
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Without knowing its purpose, it is impossible to assess whether a model’s outputs can be used to support decisions affecting the real world. Consequently, different models exist for the same system. Models therefore focus on aspects of the real system that are considered important in answering these questions. Models are developed for a specific purpose and by the need to address certain questions about real systems.
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