Courant Institute of Mathematical Sciences, New York University, New York, USA.
Institut für Mathematik, Technische Universität Berlin, Berlin, Germany.
Sci Rep. 2019 Mar 5;9(1):3505. doi: 10.1038/s41598-019-39714-0.
For centuries isolation has been the main control strategy of unforeseen epidemic outbreaks. When implemented in full and without delay, isolation is very effective. However, flawless implementation is seldom feasible in practice. We present an epidemic model called SIQ with an isolation protocol, focusing on the consequences of delays and incomplete identification of infected hosts. The continuum limit of this model is a system of Delay Differential Equations, the analysis of which reveals clearly the dependence of epidemic evolution on model parameters including disease reproductive number, isolation probability, speed of identification of infected hosts and recovery rates. Our model offers estimates on minimum response capabilities needed to curb outbreaks, and predictions of endemic states when containment fails. Critical response capability is expressed explicitly in terms of parameters that are easy to obtain, to assist in the evaluation of funding priorities involving preparedness and epidemics management.
几个世纪以来，隔离一直是应对突发疫情的主要控制策略。如果能够全面且及时地实施隔离，其效果是非常显著的。然而，在实际操作中，要做到十全十美是很难的。我们提出了一个名为 SIQ 的传染病模型，该模型带有隔离方案，重点关注延迟和不完全识别感染宿主所带来的后果。这个模型的连续极限是一个时滞微分方程系统，对其进行分析可以清楚地揭示传染病的发展与模型参数（包括疾病的繁殖数、隔离概率、感染宿主的识别速度以及恢复率）之间的关系。我们的模型提供了遏制疫情所需的最低应对能力的估计，以及在控制失败时出现地方病状态的预测。关键的应对能力是用易于获得的参数来明确表示的，以协助评估与准备和传染病管理有关的资金优先事项。
