Maugeri Andrea, Barchitta Martina, Battiato Sebastiano, Agodi Antonella
Department of Medical and Surgical Sciences and Advanced Technologies "GF Ingrassia", University of Catania, 95123 Catania, Italy.
Department of Mathematics and Computer Science, University of Catania, 95123 Catania, Italy.
J Clin Med. 2020 May 5;9(5):1350. doi: 10.3390/jcm9051350.
In the midst of the novel coronavirus (SARS-CoV-2) epidemic, examining reported case data could lead to biased speculations and conclusions. Indeed, estimation of unreported infections is crucial for a better understanding of the current emergency in China and in other countries. In this study, we aimed to estimate the unreported number of infections in China prior to the 23 January 2020 restrictions. To do this, we developed a Susceptible-Exposed-Infectious-Recovered-Dead (SEIRD) model that estimated unreported infections from the reported number of deaths. Our approach relied on the fact that observed deaths were less likely to be affected by ascertainment biases than reported infections. Interestingly, we estimated that the basic reproductive number () was 2.43 (95%CI = 2.42-2.44) at the beginning of the epidemic and that 92.9% (95%CI = 92.5%-93.1%) of total cases were not reported. Similarly, the proportion of unreported new infections by day ranged from 52.1% to 100%, with a total of 91.8% (95%CI = 91.6%-92.1%) of infections going unreported. Agreement between our estimates and those from previous studies proves that our approach is reliable for estimating the prevalence and incidence of undocumented SARS-CoV-2 infections. Once it has been tested on Chinese data, our model could be applied to other countries with different surveillance and testing policies.
在新型冠状病毒（SARS-CoV-2）疫情期间，审查报告的病例数据可能会导致有偏差的推测和结论。事实上，估计未报告的感染情况对于更好地了解中国和其他国家当前的紧急情况至关重要。在本研究中，我们旨在估计2020年1月23日实施限制措施之前中国未报告的感染人数。为此，我们开发了一种易感-暴露-感染-康复-死亡（SEIRD）模型，该模型根据报告的死亡人数来估计未报告的感染情况。我们的方法基于这样一个事实，即观察到的死亡受确诊偏倚的影响比报告的感染要小。有趣的是，我们估计疫情开始时的基本繁殖数（）为2.43（95%置信区间=2.42-2.44），并且92.9%（95%置信区间=92.5%-93.1%）的病例未被报告。同样，按日计算未报告的新感染比例在52.1%至100%之间，总共有91.8%（95%置信区间=91.6%-92.1%）的感染未被报告。我们的估计与先前研究的估计之间的一致性证明，我们的方法对于估计未记录的SARS-CoV-2感染的流行率和发病率是可靠的。一旦在中国数据上进行了测试，我们的模型可以应用于具有不同监测和检测政策的其他国家。
