Visualizing omicron: COVID-19 deaths vs. cases over time.
For most of the COVID-19 pandemic, the daily focus has been on the number of cases, and secondarily, deaths. The most recent wave was caused by the omicron variant, first identified at the end of 2021 and the dominant variant through the first part of 2022. South Africa, one of the first countries t...
| Những tác giả chính: | , |
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| Định dạng: | Bài viết |
| Ngôn ngữ: | English |
| Được phát hành: |
Public Library of Science (PLoS)
2022-01-01
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| Loạt: | PLoS ONE |
| Truy cập trực tuyến: | https://doi.org/10.1371/journal.pone.0265233 |
| _version_ | 1828012299620712448 |
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| author | Ramy Arnaout Rima Arnaout |
| author_facet | Ramy Arnaout Rima Arnaout |
| author_sort | Ramy Arnaout |
| collection | DOAJ |
| description | For most of the COVID-19 pandemic, the daily focus has been on the number of cases, and secondarily, deaths. The most recent wave was caused by the omicron variant, first identified at the end of 2021 and the dominant variant through the first part of 2022. South Africa, one of the first countries to experience and report data regarding omicron (variant 21.K), reported far fewer deaths, even as the number of reported cases rapidly eclipsed previous peaks. However, as the omicron wave has progressed, time series show that it has been markedly different from prior waves. To more readily visualize the dynamics of cases and deaths, it is natural to plot deaths per million against cases per million. Unlike the time-series plots of cases or deaths that have become daily features of pandemic updates during the pandemic, which have time as the x-axis, in a plot of deaths vs. cases, time is implicit, and is indicated in relation to the starting point. Here we present and briefly examine such plots from a number of countries and from the world as a whole, illustrating how they summarize features of the pandemic in ways that illustrate how, in most places, the omicron wave is very different from those that came before. Code for generating these plots for any country is provided in an automatically updating GitHub repository. |
| first_indexed | 2024-04-10T09:30:05Z |
| format | Article |
| id | doaj.art-9f07e7f7f5b64b89ae8f090094e19ef8 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-04-10T09:30:05Z |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-9f07e7f7f5b64b89ae8f090094e19ef82023-02-19T05:31:45ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01174e026523310.1371/journal.pone.0265233Visualizing omicron: COVID-19 deaths vs. cases over time.Ramy ArnaoutRima ArnaoutFor most of the COVID-19 pandemic, the daily focus has been on the number of cases, and secondarily, deaths. The most recent wave was caused by the omicron variant, first identified at the end of 2021 and the dominant variant through the first part of 2022. South Africa, one of the first countries to experience and report data regarding omicron (variant 21.K), reported far fewer deaths, even as the number of reported cases rapidly eclipsed previous peaks. However, as the omicron wave has progressed, time series show that it has been markedly different from prior waves. To more readily visualize the dynamics of cases and deaths, it is natural to plot deaths per million against cases per million. Unlike the time-series plots of cases or deaths that have become daily features of pandemic updates during the pandemic, which have time as the x-axis, in a plot of deaths vs. cases, time is implicit, and is indicated in relation to the starting point. Here we present and briefly examine such plots from a number of countries and from the world as a whole, illustrating how they summarize features of the pandemic in ways that illustrate how, in most places, the omicron wave is very different from those that came before. Code for generating these plots for any country is provided in an automatically updating GitHub repository.https://doi.org/10.1371/journal.pone.0265233 |
| spellingShingle | Ramy Arnaout Rima Arnaout Visualizing omicron: COVID-19 deaths vs. cases over time. PLoS ONE |
| title | Visualizing omicron: COVID-19 deaths vs. cases over time. |
| title_full | Visualizing omicron: COVID-19 deaths vs. cases over time. |
| title_fullStr | Visualizing omicron: COVID-19 deaths vs. cases over time. |
| title_full_unstemmed | Visualizing omicron: COVID-19 deaths vs. cases over time. |
| title_short | Visualizing omicron: COVID-19 deaths vs. cases over time. |
| title_sort | visualizing omicron covid 19 deaths vs cases over time |
| url | https://doi.org/10.1371/journal.pone.0265233 |
| work_keys_str_mv | AT ramyarnaout visualizingomicroncovid19deathsvscasesovertime AT rimaarnaout visualizingomicroncovid19deathsvscasesovertime |