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[西班牙新冠疫情的Gompertz曲线预测模型]

[Predictive models of the COVID-19 epidemic in Spain with Gompertz curves].

作者信息

Sánchez-Villegas Pablo, Daponte Codina Antonio

机构信息

Escuela Andaluza de Salud Pública, Granada, España; Observatorio de Salud y Medio Ambiente de Andalucía (OSMAN), Granada, España; CIBER de Epidemiología y Salud Pública (CIBERESP), España.

Escuela Andaluza de Salud Pública, Granada, España; Observatorio de Salud y Medio Ambiente de Andalucía (OSMAN), Granada, España; CIBER de Epidemiología y Salud Pública (CIBERESP), España.

出版信息

Gac Sanit. 2021 Nov-Dec;35(6):585-589. doi: 10.1016/j.gaceta.2020.05.005. Epub 2020 May 29.

DOI:10.1016/j.gaceta.2020.05.005
PMID:32680658
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7256556/
Abstract

During the international health crisis caused by the COVID-19 pandemic, it is necessary not only to know the data on infections, deaths and the occupation of hospital beds, but also to make predictions that help health authorities in the management of the crisis. The present work aims to describe the methodology used to develop predictive models of infections and deaths for the COVID-19 epidemic in Spain, based on Gompertz curves. The methodology is applied to the country as a whole and to each of its Autonomous Communities. Based on the official data available on the date of this work, and through the models described, we estimate a total of around 240.000 infected and 25.000 deaths at the end of the epidemic. At a national level, we forecast the end of the epidemic between June and July 2020.

摘要

在由新冠疫情引发的国际卫生危机期间,不仅有必要了解感染、死亡数据以及医院病床占用情况,还需要做出预测,以协助卫生当局应对危机。本研究旨在描述基于冈珀茨曲线为西班牙新冠疫情建立感染和死亡预测模型所采用的方法。该方法应用于西班牙全国及其各个自治区。根据本研究开展之日可获取的官方数据,并通过所描述的模型,我们估计疫情结束时感染总数约为24万例,死亡人数约为2.5万例。在国家层面,我们预测疫情将在2020年6月至7月结束。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cc0/7256556/67a914a433b3/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cc0/7256556/5fa506fd207a/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cc0/7256556/67a914a433b3/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cc0/7256556/5fa506fd207a/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cc0/7256556/67a914a433b3/gr2_lrg.jpg

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