Despite a range of federal and state interventions to slow the spread of COVID-19, the US has seen millions of infections and hundreds of thousands of deaths. Top-down mandates have been ineffective because the community spread of the pandemic has been influenced by complex local dynamics that have evolved over time. Systems thinking approaches, specifically causal loop diagrams, and leverage points, are important techniques for representing complexity at the local level and identifying responsive systems change opportunities. This commentary presents a causal loop diagram highlighting the progressive effects of prolonged state-level COVID-19 mandates at the community level. We also identify potential system leverage points that address these effects and present an imagined future state causal loop diagram in which these solutions are implemented. Our future system demonstrates the importance of collaborations to enable community-driven, bottom-up approaches to public health crises, such as the COVID-19 pandemic, that are adaptive and responsive to local needs.

中文翻译：

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开发基于复杂性的 COVID-19 响应以优化社区福祉：一种系统思维方法

尽管联邦和州采取了一系列干预措施来减缓 COVID-19 的传播，但美国仍有数百万人感染和数十万人死亡。自上而下的授权一直无效，因为大流行的社区传播受到了随着时间推移而演变的复杂本地动态的影响。系统思维方法，特别是因果循环图和杠杆点，是在本地表示复杂性和识别响应系统变更机会的重要技术。本评论提供了一个因果循环图，突出了社区层面延长的州级 COVID-19 授权的渐进影响。我们还确定了解决这些影响的潜在系统杠杆点，并提出了一个想象的未来状态因果循环图，其中实施了这些解决方案。