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An open-sourced, web-based application to analyze weekly excess mortality based on the Short-term Mortality Fluctuations data series.
Németh, László; Jdanov, Dmitri A; Shkolnikov, Vladimir M.
  • Németh L; Max Planck Institute for Demographic Research, Rostock, Germany.
  • Jdanov DA; Max Planck Institute for Demographic Research, Rostock, Germany.
  • Shkolnikov VM; National Research University Higher School of Economics, Moscow, Russia.
PLoS One ; 16(2): e0246663, 2021.
Article in English | MEDLINE | ID: covidwho-1067428
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Computer Graphics / Software / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Journal.pone.0246663

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Computer Graphics / Software / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Journal.pone.0246663