CONACyT - Institute of Mathematics, Universidad Nacional Autónoma de México, Juriquilla 76230, México.
Department of Automatic Control, Cinvestav-IPN, Ciudad de México 07360, México.
J R Soc Interface. 2021 May;18(178):20200803. doi: 10.1098/rsif.2020.0803. Epub 2021 May 12.
For mitigating the COVID-19 pandemic, much emphasis is made on implementing non-pharmaceutical interventions to keep the reproduction number below one. However, using that objective ignores that some of these interventions, like bans of public events or lockdowns, must be transitory and as short as possible because of their significant economic and societal costs. Here, we derive a simple and mathematically rigorous criterion for designing optimal transitory non-pharmaceutical interventions for mitigating epidemic outbreaks. We find that reducing the reproduction number below one is sufficient but not necessary. Instead, our criterion prescribes the required reduction in the reproduction number according to the desired maximum of disease prevalence and the maximum decrease of disease transmission that the interventions can achieve. We study the implications of our theoretical results for designing non-pharmaceutical interventions in 16 cities and regions during the COVID-19 pandemic. In particular, we estimate the minimal reduction of each region's contact rate necessary to control the epidemic optimally. Our results contribute to establishing a rigorous methodology to design optimal non-pharmaceutical intervention policies for mitigating epidemic outbreaks.
为缓解 COVID-19 大流行,人们非常重视实施非药物干预措施,将繁殖数保持在 1 以下。然而,使用该目标忽略了这些干预措施中的一些,例如禁止公共活动或封锁,由于其巨大的经济和社会成本,这些干预措施必须是暂时的和尽可能短的。在这里,我们为缓解传染病爆发而设计最优过渡性非药物干预措施导出了一个简单而严格的数学准则。我们发现,将繁殖数降低到 1 以下是足够的,但不是必需的。相反,我们的准则根据干预措施所能达到的最大疾病流行和最大疾病传播减少,规定了所需的繁殖数减少量。我们研究了我们的理论结果对设计 COVID-19 大流行期间 16 个城市和地区的非药物干预措施的影响。特别是,我们估计了每个地区为了最优控制疫情所需的最小接触率降低。我们的结果有助于建立一种严格的方法来设计缓解传染病爆发的最优非药物干预政策。