Living With COVID-19: A Systemic and Multi-Criteria Approach to Enact Evidence-Based Health Policy
Living With COVID-19: A Systemic and Multi-Criteria Approach to Enact Evidence-Based Health Policy
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DOI：
10.3389/fpubh.2020.00294
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发表时间：
2020-06-16
影响因子：
5.2
通讯作者：
Lhermie, Guillaume
中科院分区：
文献类型：
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作者：
Raboisson, Didier;Lhermie, Guillaume
解除COVID-19（2019冠状病毒病）封锁需要在短期和中期内采取全面和循证的人口健康管理方法，该方法基于结合风险因素和生物经济结果，包括行为者的行为。这种动态和全球性的健康控制方法对于应对感染性疾病的新范式是必要的，这种新范式破坏了我们的个人自由和行为。政策制定者面临的挑战包括确定解除封锁和后续行动（中期规则）的方法，这些方法最能满足恢复经济活动、社会福祉和遏制疫情的需要。没有简单易用的方法来做到这一点，因为这意味着同时考虑几个相互竞争的目标，并不断调整战略和规则，最好是在当地范围内。我们提出了一个框架，以创建一个精确的循证卫生政策，同时考虑公共卫生，经济和社会层面，同时考虑到限制和不确定性。它是基于以下四个原则：集成多个和异构的信息，接受导航的不确定性，动态调整策略的反馈机制，并通过多标量概念管理集群。通过流行病学模型和生物经济学模型获得的基于证据的COVID-19政策干预包括科学背景。一套定量和定性指标被用作反馈，以精确监测社会-经济-流行病动态，从而在流行病损害（再次）发生之前收紧或放松措施。总而言之，这使得基于证据的政策能够精确地指导战略，避免任何政治冲击。
The lifting of COVID-19 (coronavirus disease 2019) lockdown requires, in the short and medium terms, a holistic and evidence-based approach to population health management based on combining risk factors and bio-economic outcomes, including actors' behaviors. This dynamic and global approach to health control is necessary to deal with the new paradigm of living with an infectious disease, which disrupts our individual freedom and behaviors. The challenge for policymakers consists of defining methods of lockdown-lifting and follow-up (middle-term rules) that best meet the needs for resumption of economic activity, societal wellbeing, and containment of the outbreak. There is no simple and ready-to-use way to do this since it means considering several competing objectives at the same time and continuously adapting the strategy and rules, ideally at local scale. We propose a framework for creating a precision evidence-based health policy that simultaneously considers public health, economic, and societal dimensions while accounting for constraints and uncertainty. It is based on the four following principles: integrating multiple and heterogeneous information, accepting navigation with uncertainty, adjusting the strategy dynamically with feedback mechanisms, and managing clusters through a multi-scalar conception. The evidence-based policy intervention for COVID-19 obtained includes scientific background via epidemiological modeling and bio-economic modeling. A set of quantitative and qualitative indicators are used as feedback to precisely monitor the societal-economic-epidemiological dynamics, allowing tightening or loosening of measures before epidemic damage (re-)occurs. Altogether, this allows an evidence-based policy that steers the strategy with precision and avoids any political shock.