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基于大流行期间新感染人数预测住院和死亡人数的方法。

A method for forecasting the number of hospitalized and deceased based on the number of newly infected during a pandemic.

机构信息

Department of Mathematics, University of Osijek, 31 000, Osijek, Croatia.

Department of Mathematics, University of Zagreb, 10 000, Zagreb, Croatia.

出版信息

Sci Rep. 2022 Mar 21;12(1):4773. doi: 10.1038/s41598-022-08795-9.

Abstract

In this paper we propose a phenomenological model for forecasting the numbers of deaths and of hospitalized persons in a pandemic wave, assuming that these numbers linearly depend, with certain delays [Formula: see text] for deaths and [Formula: see text] for hospitalized, on the number of new cases. We illustrate the application of our method using data from the third wave of the COVID-19 pandemic in Croatia, but the method can be applied to any new wave of the COVID-19 pandemic, as well as to any other possible pandemic. We also supply freely available Mathematica modules to implement the method.

摘要

在本文中,我们提出了一种基于现象学的模型,用于预测大流行浪潮中的死亡人数和住院人数,假设这些数字与新发病例数呈线性关系,死亡人数的延迟时间为[Formula: see text],住院人数的延迟时间为[Formula: see text]。我们使用来自克罗地亚 COVID-19 大流行第三波的数据说明了我们方法的应用,但该方法可应用于 COVID-19 大流行的任何新波,也可应用于任何其他可能的大流行。我们还提供了免费的 Mathematica 模块来实现该方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bb63/8938470/079c5a43dc44/41598_2022_8795_Fig1_HTML.jpg

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