Sebastiani Giovanni, Spassiani Ilaria
Istituto per le Applicazioni del Calcolo Mauro Picone, Consiglio Nazionale delle Ricerche, Via dei Taurini 19, 00185 Rome, Italy.
Mathematics Department "Guido Castelnuovo", Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy.
Vaccines (Basel). 2022 Oct 25;10(11):1788. doi: 10.3390/vaccines10111788.
In this paper, we deal with the problem of estimating the reproduction number Rt during an epidemic, as it represents one of the most used indicators to study and control this phenomenon. In particular, we focus on two issues. First, to estimate Rt, we consider the use of positive test case data as an alternative to the first symptoms data, which are typically used. We both theoretically and empirically study the relationship between the two approaches. Second, we modify a method for estimating Rt during an epidemic that is widely used by public institutions in several countries worldwide. Our procedure is not affected by the problems deriving from the hypothesis of Rt local constancy, which is assumed in the standard approach. We illustrate the results obtained by applying the proposed methodologies to real and simulated SARS-CoV-2 datasets. In both cases, we also apply some specific methods to reduce systematic and random errors affecting the data. Our results show that the Rt during an epidemic can be estimated by using the positive test data, and that our estimator outperforms the standard estimator that makes use of the first symptoms data. It is hoped that the techniques proposed here could help in the study and control of epidemics, particularly the current SARS-CoV-2 pandemic.
在本文中，我们探讨了在疫情期间估计再生数Rt的问题，因为它是研究和控制这一现象时最常用的指标之一。具体而言，我们关注两个问题。首先，为了估计Rt，我们考虑使用阳性检测病例数据来替代通常使用的首次出现症状的数据。我们从理论和实证两方面研究了这两种方法之间的关系。其次，我们改进了一种在疫情期间估计Rt的方法，该方法在全球多个国家的公共机构中广泛使用。我们的方法不受标准方法中所假设的Rt局部恒定假设所产生问题的影响。我们阐述了将所提出的方法应用于真实和模拟的SARS-CoV-2数据集所获得的结果。在这两种情况下，我们还应用了一些特定方法来减少影响数据的系统误差和随机误差。我们的数据表明，在疫情期间可以通过使用阳性检测数据来估计Rt，并且我们的估计器优于使用首次出现症状数据的标准估计器。希望这里提出的技术能够有助于疫情的研究和控制，特别是当前的SARS-CoV-2大流行。
