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.

中文翻译：

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解决大流行性健康-经济困境的最佳控制策略

非药物干预措施（NPI）是遏制大流行的有效措施。但是，此类控制措施通常会对经济产生负面影响。在这里，我们提出了一种宏观层面的方法来支持解决这一健康-经济困境（HED）。首先，建议对包括经济模型在内的众所周知的SEIR模型进行扩展。其次，定义了一个双目标优化问题，以针对HED问题研究最优控制策略。接下来，应用几种多目标进化算法对获得的最优策略所固有的健康-经济绩效权衡进行研究。最后，将来自所应用算法的结果进行比较，以选择用于将来研究的优选算法。不出所料，对于建议的模型和策略，在健康和经济表现之间发现了明显的冲突。此外，结果表明，与完全不采用此类策略相比，NPI的指导性使用更为可取。这项研究通过提供一种新颖的概念，有助于大流行病的建模和模拟，该概念详尽阐述了整合经济方面的问题，同时探索了启用NPI的最佳时机。