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一种估计即时病死率的简单方法:以加拿大公开的新冠疫情监测数据为例。

A simple approach to estimate the instantaneous case fatality ratio: Using the publicly available COVID-19 surveillance data in Canada as an example.

作者信息

Zhao Shi

机构信息

Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China.

School of Nursing, Hong Kong Polytechnic University, Hong Kong, China.

出版信息

Infect Dis Model. 2020;5:575-579. doi: 10.1016/j.idm.2020.08.002. Epub 2020 Aug 15.

Abstract

The case fatality ratio (CFR) is one of the key measurements to evaluate the clinical severity of infectious diseases. The CFR may vary due to change in factors that affect the mortality risk. In this study, we developed a simple likelihood-based framework to estimate the instantaneous CFR of infectious diseases. We used the publicly available COVID-19 surveillance data in Canada for demonstration. We estimated the mean fatality ratio of reported COVID-19 cases (rCFR) in Canada was estimated at 6.9% (95%CI: 4.5-10.6). We emphasize the extensive implementation of the constructed instantaneous CFR that is to identify the key determinants affecting the mortality risk.

摘要

病死率(CFR)是评估传染病临床严重程度的关键指标之一。病死率可能会因影响死亡风险的因素变化而有所不同。在本研究中,我们开发了一个基于似然性的简单框架来估计传染病的即时病死率。我们使用加拿大公开的新冠肺炎监测数据进行演示。我们估计加拿大报告的新冠肺炎病例的平均病死率(rCFR)为6.9%(95%置信区间:4.5-10.6)。我们强调广泛应用构建的即时病死率以识别影响死亡风险的关键决定因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9508/7452652/110486e10d2f/gr1.jpg

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