论文标题
智能测试和选择性隔离，以控制流行病
Smart Testing and Selective Quarantine for the Control of Epidemics
论文作者
论文摘要
本文基于以下观察结果：在Covid-19-19流行期间，应测试个人的选择对选择性约束措施的有效性具有重要影响。这个决策问题与最佳传感器选择问题密切相关，这是控制工程中非常活跃的研究主题。本文的目的是提出一项政策，以巧妙地选择要测试的个人。主要思想是将流行病作为随机动态系统建模，并选择要根据某些最佳标准进行相应测试的个体，例如为了最大程度地减少未发现无症状病例的可能性。每天，不同个体感染的可能性都会更新，以利用前几天现象的随机模型以及收集的信息。对10000个人的封闭社区的仿真表明，与选择性的限制政策相比，该技术以及选择性限制政策可以减少疾病的传播，同时与基于接触数量的正面接触式跟踪和离线测试选择策略相比，限制了被限制的个体数量。
This paper is based on the observation that, during Covid-19 epidemic, the choice of which individuals should be tested has an important impact on the effectiveness of selective confinement measures. This decision problem is closely related to the problem of optimal sensor selection, which is a very active research subject in control engineering. The goal of this paper is to propose a policy to smartly select the individuals to be tested. The main idea is to model the epidemics as a stochastic dynamic system and to select the individual to be tested accordingly to some optimality criteria, e.g. to minimize the probability of undetected asymptomatic cases. Every day, the probability of infection of the different individuals is updated making use of the stochastic model of the phenomenon and of the information collected in the previous days. Simulations for a closed community of 10000 individuals show that the proposed technique, coupled with a selective confinement policy, can reduce the spread of the disease while limiting the number of individuals confined if compared to the simple contact tracing of positive and to an off-line test selection strategy based on the number of contacts.
