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关于新病毒爆发初期的最优控制

On optimal control at the onset of a new viral outbreak.

作者信息

Smirnova Alexandra, Ye Xiaojing

机构信息

Department of Mathematics & Statistics, Georgia State University, Atlanta, USA.

出版信息

Infect Dis Model. 2024 May 15;9(4):995-1006. doi: 10.1016/j.idm.2024.05.006. eCollection 2024 Dec.

Abstract

We propose a versatile model with a flexible choice of control for an early-pandemic outbreak prevention when vaccine/drug is not yet available. At that stage, control is often limited to non-medical interventions like social distancing and other behavioral changes. For the SIR optimal control problem, we show that the running cost of control satisfying mild, practically justified conditions generates an optimal strategy, (),  ∈ [0, ], that is sustainable up until some moment  ∈ [0, ). However, for any  ∈ [, ], the function () will decline as approaches , which may cause the number of newly infected people to increase. So, the window from 0 to is the time for public health officials to prepare alternative mitigation measures, such as vaccines, testing, antiviral medications, and others. In addition to theoretical study, we develop a fast and stable computational method for solving the proposed optimal control problem. The efficiency of the new method is illustrated with numerical examples of optimal control trajectories for various cost functions and weights. Simulation results provide a comprehensive demonstration of the effects of control on the epidemic spread and mitigation expenses, which can serve as invaluable references for public health officials.

摘要

我们提出了一种通用模型,在尚无疫苗/药物的情况下,可为大流行早期爆发预防提供灵活的控制选择。在那个阶段,控制措施通常限于非医疗干预,如社交距离和其他行为改变。对于SIR最优控制问题,我们表明,满足温和且实际合理条件的控制运行成本会产生一种最优策略,即((\cdot)),(\cdot\in[0,\cdot]),该策略在某个时刻(\cdot\in[0,\cdot])之前都是可持续的。然而,对于任何(\cdot\in[\cdot,\cdot]),随着(\cdot)趋近于(\cdot),函数((\cdot))将会下降,这可能导致新感染人数增加。所以,从0到(\cdot)的这段时间是公共卫生官员准备替代缓解措施的时机,如疫苗、检测、抗病毒药物等。除了理论研究,我们还开发了一种快速且稳定的计算方法来求解所提出的最优控制问题。通过针对各种成本函数和权重的最优控制轨迹的数值示例,说明了新方法的效率。模拟结果全面展示了控制措施对疫情传播和缓解成本的影响,可为公共卫生官员提供宝贵参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5985/11222799/52cdd25298a8/gr1.jpg

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