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基于分层的 COVID-19 暴发病例病死率估计。

Estimation of the case fatality rate based on stratification for the COVID-19 outbreak.

机构信息

Department of Statistics, Seoul National University, Seoul, Republic of Korea.

出版信息

PLoS One. 2021 Feb 22;16(2):e0246921. doi: 10.1371/journal.pone.0246921. eCollection 2021.

Abstract

This work is motivated by the recent worldwide pandemic of the novel coronavirus disease (COVID-19). When an epidemiological disease is prevalent, estimating the case fatality rate, the proportion of deaths out of the total cases, accurately and quickly is important as the case fatality rate is one of the crucial indicators of the risk of a disease. In this work, we propose an alternative estimator of the case fatality rate that provides more accurate estimate during an outbreak by reducing the downward bias (underestimation) of the naive CFR, the proportion of deaths out of confirmed cases at each time point, which is the most commonly used estimator due to the simplicity. The proposed estimator is designed to achieve the availability of real-time update by using the commonly reported quantities, the numbers of confirmed, cured, deceased cases, in the computation. To enhance the accuracy, the proposed estimator adapts a stratification, which allows the estimator to use information from heterogeneous strata separately. By the COVID-19 cases of China, South Korea and the United States, we numerically show the proposed stratification-based estimator plays a role of providing an early warning about the severity of a epidemiological disease that estimates the final case fatality rate accurately and shows faster convergence to the final case fatality rate.

摘要

这项工作的动机是最近全球新型冠状病毒病 (COVID-19) 的流行。当一种传染病流行时,准确、快速地估计病死率(总病例中死亡人数的比例)非常重要,因为病死率是疾病风险的关键指标之一。在这项工作中,我们提出了一种病死率的替代估计方法,通过减少因数据简单而最常用的估计方法——每个时间点确诊病例中死亡比例(即单纯病死率)的低估(即低估),在疫情爆发期间提供更准确的估计。该估计器旨在通过使用计算中常用的确诊、治愈和死亡病例数等报告数量来实现实时更新的可用性。为了提高准确性,所提出的估计器采用了一种分层方法,允许估计器分别使用来自不同层的信息。通过中国、韩国和美国的 COVID-19 病例,我们数值地表明,所提出的基于分层的估计器在提供有关传染病严重程度的早期预警方面发挥了作用,它可以准确估计最终病死率,并更快地收敛到最终病死率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7082/7899354/7bac2f94752c/pone.0246921.g001.jpg

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