论文标题
估算SARS-COV-2流行病的临界参数的样本方法：一种操作设计
A sample approach to the estimation of the critical parameters of the SARS-CoV-2 epidemics: an operational design
论文作者
论文摘要
鉴于与COVID-19大流行有关感染的扩散有关的紧急信息需求，在本文中，我们提出了一种用于构建连续时间监视系统的抽样设计。与其他观察策略相比，所提出的方法具有三个重要的力量和原创性要素：（i）它的目的是在一次时刻提供现象的快照，并且它被设计为随着时间的推移在几个波动中重复进行的连续调查，在考虑流行病的不同阶段，在不同的目标变量中进行了不同的目标变量； （ii）通过Monte Carlo实验正式得出并测试了所提出的估计量的统计最佳性能； （iii）它迅速运行，因为与病毒扩散有关的紧急情况需要此特性。采样设计被认为是在2020年春季在意大利的SAR-COV-2扩散而设计的。但是，这是非常笼统的，我们有信心它可以轻松扩展到其他地理区域，并可能将来可能的流行病爆发。正式的证明和蒙特卡洛演习强调，估计器是公正的，并且比简单的随机抽样方案具有更高的效率。
Given the urgent informational needs connected with the diffusion of infection with regard to the COVID-19 pandemic, in this paper, we propose a sampling design for building a continuous-time surveillance system. Compared with other observational strategies, the proposed method has three important elements of strength and originality: (i) it aims to provide a snapshot of the phenomenon at a single moment in time, and it is designed to be a continuous survey that is repeated in several waves over time, taking different target variables during different stages of the development of the epidemic into account; (ii) the statistical optimality properties of the proposed estimators are formally derived and tested with a Monte Carlo experiment; and (iii) it is rapidly operational as this property is required by the emergency connected with the diffusion of the virus. The sampling design is thought to be designed with the diffusion of SAR-CoV-2 in Italy during the spring of 2020 in mind. However, it is very general, and we are confident that it can be easily extended to other geographical areas and to possible future epidemic outbreaks. Formal proofs and a Monte Carlo exercise highlight that the estimators are unbiased and have higher efficiency than the simple random sampling scheme.
