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COVID-19 case fatality-derived risk of death adjusted by age and gender

Authors: Alexander Yuryatin;

COVID-19 case fatality-derived risk of death adjusted by age and gender

Abstract

This figure plots the risk of death in COVID-19 adjusted by the age and gender, which was modeled with the case fatality data kindly collected by the team of data scientists and data engineers in the Kaggle project Data Science for COVID-19 in South Korea (DS4C), which is hosted at https://www.kaggle.com/kimjihoo/coronavirusdataset. The model for the plot was built with the release 2.2 of the open-sourced Python & C library for macOS and Linux initially published under GPLv3 license on April 3, 2020, on GitHub at https://github.com/yuryatin/covid19_age_adjusted_mortality. Please, visit https://github.com/yuryatin/covid19_age_adjusted_mortality for more detailed description of the model and for the source code.

Keywords

probability of death, risk of death by age, ds4c, coronavirus, age-adjusted case fatality, risk of death by age and gender, risk of death, covid, mortality rate, age-adjusted case mortality by gender, age-adjusted case fatality by gender, mortality by age, age-adjusted mortality, covid19, data science for covid-19, korean, covid-19, death rate, case fatality, mortality by age and gender

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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