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一个开源的、基于网络的应用程序,用于根据短期死亡率波动数据系列分析每周超额死亡率。

An open-sourced, web-based application to analyze weekly excess mortality based on the Short-term Mortality Fluctuations data series.

机构信息

Max Planck Institute for Demographic Research, Rostock, Germany.

National Research University Higher School of Economics, Moscow, Russia.

出版信息

PLoS One. 2021 Feb 5;16(2):e0246663. doi: 10.1371/journal.pone.0246663. eCollection 2021.

Abstract

The COVID-19 pandemic stimulated the interest of scientists, decision makers and the general public in short-term mortality fluctuations caused by epidemics and other natural or man-made disasters. To address this interest and provide a basis for further research, in May 2020, the Short-term Mortality Fluctuations data series was launched as a new section of the Human Mortality Database. At present, this unique data resource provides weekly mortality death counts and rates by age and sex for 38 countries and regions. The main objective of this paper is to detail the web-based application for visualizing and analyzing the excess mortality based on the Short-term Mortality Fluctuation data series. The application yields a visual representation of the database that enhances the understanding of the underlying data. Besides, it enables the users to explore data on weekly mortality and excess mortality across years and countries. The contribution of this paper is twofold. First, to describe a visualization tool that aims to facilitate research on short-term mortality fluctuations. Second, to provide a comprehensive open-source software solution for demographic data to encourage data holders to promote their datasets in a visual framework.

摘要

新冠疫情刺激了科学家、决策者和公众对由流行病和其他自然或人为灾害引起的短期死亡率波动的兴趣。为了满足这一兴趣,并为进一步的研究提供基础,2020 年 5 月,短期死亡率波动数据系列作为人类死亡率数据库的一个新部分推出。目前,这个独特的数据资源每周提供 38 个国家和地区按年龄和性别划分的死亡率死亡人数和死亡率。本文的主要目的是详细介绍基于短期死亡率波动数据系列的可视化和分析超额死亡率的网络应用程序。该应用程序提供了数据库的可视化表示,增强了对基础数据的理解。此外,它还使用户能够探索多年来不同国家的每周死亡率和超额死亡率数据。本文的贡献有两点。首先,描述了一个旨在促进短期死亡率波动研究的可视化工具。其次,提供了一个全面的开源人口统计数据解决方案,以鼓励数据持有者以可视化框架来推广他们的数据集。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1aa4/7864412/12ab4f866c43/pone.0246663.g001.jpg

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