论文标题
最佳干预策略，以最大程度地减少流行病的总发病率
Optimal intervention strategies for minimizing total incidence during an epidemic
论文作者
论文摘要
本文认为，在流行病的过程中，受感染个体的总数最小化，在这种流行病的过程中，通过时间依赖性的非药物干预措施可以降低传染性接触率。干预措施的社会和经济成本使用线性预算约束来考虑，该预算约束在短期重型干预和长期光线干预措施之间实现权衡。我们在包含多个连续锁定，逐渐强加和解除限制的控制空间的无限尺寸空间中寻找最佳干预策略，以及基于跟踪有效复制数字的各种启发式控件。数学分析表明，在所有此类策略中，全局最优值是通过最大可能幅度的单个恒定级别锁定来实现的。数值模拟强调了需要仔细的这种干预时机的需求，并说明了与旨在最大程度降低峰值患病率的策略相比，它们的益处和缺点。相反，违反直觉，在开始精心计划的干预策略开始之前增加限制甚至可能会增加总发病率。
This article considers the minimization of the total number of infected individuals over the course of an epidemic in which the rate of infectious contacts can be reduced by time-dependent nonpharmaceutical interventions. The societal and economic costs of interventions are taken into account using a linear budget constraint which imposes a trade-off between short-term heavy interventions and long-term light interventions. We search for an optimal intervention strategy in an infinite-dimensional space of controls containing multiple consecutive lockdowns, gradually imposed and lifted restrictions, and various heuristic controls based for example on tracking the effective reproduction number. Mathematical analysis shows that among all such strategies, the global optimum is achieved by a single constant-level lockdown of maximum possible magnitude. Numerical simulations highlight the need of careful timing of such interventions, and illustrate their benefits and disadvantages compared to strategies designed for minimizing peak prevalence. Rather counterintuitively, adding restrictions prior to the start of a well-planned intervention strategy may even increase the total incidence.
