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covid19.Explorer: a web application and R package to explore United States COVID-19 data
Appearing at the end of 2019, a novel virus (later identified as SARS-CoV-2) was characterized in the city of Wuhan in Hubei Province, China. As of the time of writing, the disease caused by this virus (known as COVID-19) has already resulted in over three million deaths worldwide. SARS-CoV-2 infect...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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PeerJ Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8381881/ https://www.ncbi.nlm.nih.gov/pubmed/34484978 http://dx.doi.org/10.7717/peerj.11489 |
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author | Revell, Liam J. |
author_facet | Revell, Liam J. |
author_sort | Revell, Liam J. |
collection | PubMed |
description | Appearing at the end of 2019, a novel virus (later identified as SARS-CoV-2) was characterized in the city of Wuhan in Hubei Province, China. As of the time of writing, the disease caused by this virus (known as COVID-19) has already resulted in over three million deaths worldwide. SARS-CoV-2 infections and deaths, however, have been highly unevenly distributed among age groups, sexes, countries, and jurisdictions over the course of the pandemic. Herein, I present a tool (the covid19.Explorer R package and web application) that has been designed to explore and analyze publicly available United States COVID-19 infection and death data from the 2020/21 U.S. SARS-CoV-2 pandemic. The analyses and visualizations that this R package and web application facilitate can help users better comprehend the geographic progress of the pandemic, the effectiveness of non-pharmaceutical interventions (such as lockdowns and other measures, which have varied widely among U.S. states), and the relative risks posed by COVID-19 to different age groups within the U.S. population. The end result is an interactive tool that will help its users develop an improved understanding of the temporal and geographic dynamics of the SARS-CoV-2 pandemic, accessible to lay people and scientists alike. |
format | Online Article Text |
id | pubmed-8381881 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83818812021-09-02 covid19.Explorer: a web application and R package to explore United States COVID-19 data Revell, Liam J. PeerJ Bioinformatics Appearing at the end of 2019, a novel virus (later identified as SARS-CoV-2) was characterized in the city of Wuhan in Hubei Province, China. As of the time of writing, the disease caused by this virus (known as COVID-19) has already resulted in over three million deaths worldwide. SARS-CoV-2 infections and deaths, however, have been highly unevenly distributed among age groups, sexes, countries, and jurisdictions over the course of the pandemic. Herein, I present a tool (the covid19.Explorer R package and web application) that has been designed to explore and analyze publicly available United States COVID-19 infection and death data from the 2020/21 U.S. SARS-CoV-2 pandemic. The analyses and visualizations that this R package and web application facilitate can help users better comprehend the geographic progress of the pandemic, the effectiveness of non-pharmaceutical interventions (such as lockdowns and other measures, which have varied widely among U.S. states), and the relative risks posed by COVID-19 to different age groups within the U.S. population. The end result is an interactive tool that will help its users develop an improved understanding of the temporal and geographic dynamics of the SARS-CoV-2 pandemic, accessible to lay people and scientists alike. PeerJ Inc. 2021-08-20 /pmc/articles/PMC8381881/ /pubmed/34484978 http://dx.doi.org/10.7717/peerj.11489 Text en © 2021 Revell https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Revell, Liam J. covid19.Explorer: a web application and R package to explore United States COVID-19 data |
title | covid19.Explorer: a web application and R package to explore United States COVID-19 data |
title_full | covid19.Explorer: a web application and R package to explore United States COVID-19 data |
title_fullStr | covid19.Explorer: a web application and R package to explore United States COVID-19 data |
title_full_unstemmed | covid19.Explorer: a web application and R package to explore United States COVID-19 data |
title_short | covid19.Explorer: a web application and R package to explore United States COVID-19 data |
title_sort | covid19.explorer: a web application and r package to explore united states covid-19 data |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8381881/ https://www.ncbi.nlm.nih.gov/pubmed/34484978 http://dx.doi.org/10.7717/peerj.11489 |
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