Visualizing the Corona (COVID-19) pandemic

Where does the data come frome?

The analyses and visualizations are based on the data provided by the John Hopkins University in the Official 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository. The same data sets are used to constantly update this visual dashboard: https://coronavirus.jhu.edu/map.html

IMPORTANT DISCLAIMER: Although I do believe that these data help us to understand the pandemic, they are nonetheless very imprecise. When we want to make sense of positive test results (i.e., total cases and in the long run mortality rates and recovering processes), we need to know how many tests were conducted (for more information on this, see this article in Science).

Furthermore, I would like to emphasize that I am not an expert on epidemology or virus outbreaks and I am not working in the health sector. On this page, I am only visualizing the data by the John Hopkins University. Reliance on the these visualizations for medical guidance or use of these visualization in commerce is strictly prohibited.

Will these figures be updated?

The last update was made on 2022-04-12 07:52:11. The data of the John Hopkins University, however, are always updated at 23:59. What you see is hence the situation on 2022-04-11 at 23:59:00. Also bear in mind that the reporting of cases is somewhat delayed so that it is very likely that the actual numbers are higher.

Visualizations

If you are interested in the R code, please see the README.rmd.

1. Daily new cases

The blue line is the moving average of new cases per 7 days. The grey bars represent the new cases per day.

Europe

America

Middle East

Asia

Africa

2. Comparing visualizations

One thing that is constantly debatted is how to visualize the growth of total confirmed cases at all. Log-transform the y-axis or not? Plot against the date? Plot against days after 100th case? Plot something entirely different?

Here, I would like to explain some differences between visualizations that have been used in the media or on Twitter. All of them are helpful in their own regard.

1. LEFT: Here, I plotted total cases against days after the 100th cases without logarithmizing the y-axis.

2. MIDDLE: The y-axis is logarithmized. This figure is often shown in the news.

3. RIGHT: New cases per 7 days (y-axis) are plotted against total cases (x-axis), both axes are logarithmized (Idea explained in this video).

Note: Green = USA, Blue = Italy, Red = Germany, Pink = Austria, Orange = United Kingdom