Université de Toulouse, INRA, ENVT, Toulouse, France.
Front Public Health. 2020 Nov 17;8:606371. doi: 10.3389/fpubh.2020.606371. eCollection 2020.
As of mid-2020, eradicating COVID-19 seems not to be an option, at least in the short term. The challenge for policy makers consists of implementing a suitable approach to contain the outbreak and limit extra deaths without exhausting healthcare forces while mitigating the impact on the country's economy and on individuals' well-being. To better describe the trade-off between the economic, societal and public health dimensions, we developed an integrated bioeconomic optimization approach. We built a discrete age-structured model considering three main populations (youth, adults and seniors) and 8 socio-professional characteristics for the adults. Fifteen lockdown exit strategies were simulated for several options: abrupt or progressive (4 or 8 weeks) lockdown lift followed by total definitive transitory final unlocking. Three values of transmission rate (Tr) were considered to represent individuals' barrier gesture compliance. Optimization under constraint to find the best combination of scenarios and options was performed on the minimal total cost for production losses due to contracted activities and hospitalization in the short and mid-term, with 3 criteria: mortality, person-days locked and hospital saturation. The results clearly show little difference between the scenarios based on the economic impact or the 3 criteria. This means that policy makers should focus on individuals' behaviors (represented by the Tr value) more than on trying to optimize the lockdown strategy (defining who is unlocked and who is locked). For a given Tr, the choices of scenarios permit the management of the hospital saturation level with regard to both its intensity and its duration, which remains a key point for public health. The results highlight the need for behavioral or experimental economics to address COVID-19 issues through a better understanding of individual behavior motivations and the identification of ways to improve biosecurity compliance.
截至 2020 年年中，消除 COVID-19 似乎不是一个选择，至少在短期内是这样。政策制定者面临的挑战是实施一种合适的方法来控制疫情并限制额外的死亡人数，同时避免耗尽医疗资源，减轻对国家经济和个人福祉的影响。为了更好地描述经济、社会和公共卫生方面的权衡，我们开发了一种综合的生物经济优化方法。我们建立了一个离散的年龄结构模型，考虑了三个主要人群（青年、成年人和老年人）和成年人的 8 种社会职业特征。对于几种选择，模拟了 15 种封锁退出策略：突然或渐进（4 或 8 周）封锁解除，然后是完全最终过渡性最终解锁。考虑了三种传播率（Tr）值来代表个体的屏障行为合规性。在约束条件下进行优化，以找到最佳的场景和选择组合，目标是最小化短期和中期因合同活动和住院而导致的生产损失总成本，使用了 3 个标准：死亡率、锁定天数和医院饱和度。结果清楚地表明，基于经济影响或 3 个标准的场景之间几乎没有差异。这意味着政策制定者应该更加关注个体行为（由 Tr 值表示），而不是试图优化封锁策略（定义谁被解锁，谁被锁定）。对于给定的 Tr 值，场景的选择可以管理医院饱和度水平，包括其强度和持续时间，这仍然是公共卫生的一个关键点。结果强调了需要通过更好地理解个体行为动机和确定提高生物安全合规性的方法，来利用行为或实验经济学来解决 COVID-19 问题。
