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利用感染源测量评估暴发中未诊断感染的数量。

Evaluation of the number of undiagnosed infected in an outbreak using source of infection measurements.

机构信息

Department of Mathematics, Bar-Ilan University, 52900, Ramat Gan, Israel.

Gonda Brain Research Center, Bar-Ilan University, 52900, Ramat Gan, Israel.

出版信息

Sci Rep. 2021 Feb 11;11(1):3601. doi: 10.1038/s41598-021-82691-6.

Abstract

In times of outbreaks, an essential requirement for better monitoring is the evaluation of the number of undiagnosed infected individuals. An accurate estimate of this fraction is crucial for the assessment of the situation and the establishment of protective measures. In most current studies using epidemics models, the total number of infected is either approximated by the number of diagnosed individuals or is dependent on the model parameters and assumptions, which are often debated. We here study the relationship between the fraction of diagnosed infected out of all infected, and the fraction of infected with known contaminator out of all diagnosed infected. We show that those two are approximately the same in exponential models and across most models currently used in the study of epidemics, independently of the model parameters. As an application, we compute an estimate of the effective number of infected by the SARS-CoV-2 virus in various countries.

摘要

在疫情爆发时期,更好地监测疫情的一个基本要求是评估未确诊的感染者数量。准确估计这部分感染者的数量对于评估疫情情况和采取保护措施至关重要。在大多数目前使用传染病模型的研究中,感染总人数要么通过确诊人数来近似估计,要么取决于模型参数和假设,而这些参数和假设往往存在争议。在这里,我们研究了已诊断感染者中确诊感染者的比例与所有已诊断感染者中已知传染源感染者的比例之间的关系。我们发现,在指数模型中以及在目前用于传染病研究的大多数模型中,这两个比例大致相同,与模型参数无关。作为一个应用,我们计算了 SARS-CoV-2 病毒在不同国家的有效感染者数量的估计值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbff/7878881/9aab7c5dae3e/41598_2021_82691_Fig1_HTML.jpg

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