COVID-19 Open Source Dashboard
By: Christoph Schönenberger
Tags: R, Open Source, Covid 19, Data Science, Data Visualization

COVID-19 Open Source Dashboard

As data scientists, we must do our best to approach the current COVID-19 pandemic from a data perspective. Therefore, I have created a dashboard using open source tools to track and visualize the spread of COVID-19.

The COVID-19 pandemic has been an unavoidable topic for several weeks now. Media is flooding us with breaking news on newly infected celebrities, exponential growth of cases and deaths in several countries. People on social media cannot talk about anything else these days and videos of toilet paper hoarders go viral.

Companies did not miss this trend. In the past few days, my Twitter and LinkedIn feeds have been cluttered with companies showing how great their technology is and how selfless they use it to support government agencies, health care facilities and the like. Do not get me wrong, I think it is awesome that companies are willing to help; kudos to every company that offers assistance to any public institution that needs help in this current crisis! However, if each of these contributions has to be fully exploited in terms of marketing, they leave a stale taste in their wake.

Additionally, the most popular dashboard uses a black and red coloring schema that encourages fearmongering, just like various news pages with their shocking headlines. Visualizations do matter, and as data scientists, we should be well aware of this as outlined in this article. I knew that it is possible to create a less alarmist dashboard that is on-par with most popular COVID-19 dashboards using open source technology such as R Shiny or Python Dash, all in a couple of hours. And that’s exactly what I did! You can find the R Shiny dashboard I created here.

Data

The data that was used for all visualizations was provided by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) who shared their data on a public Github page. The Johns Hopkins CSSE aggregates data from primary sources, such as the World Health Organisation, national, and regional public health institutions. This data is made freely available and is updated every day.

The population data used in the dashboard is sourced from the World Bank Open Data. The data only needed some minor tinkering to fit the Johns Hopkins CSSE COVID-19 data. The population for “countries” which were not available in the dataset (mostly insular entities) was added manually with data from Wikipedia. The World Bank has a large data repository covering various topics, from gender statistics to investment flows. This repository is highly accessible, either by using their API directly or one of the various third-party APIs which are available in most common programming languages. This provides us the opportunity to integrate various interesting data sets in the dashboard that are currently not included in the “mainstream” options. You can find more information for developers here.

The COVID-19 Dashboard — Open Source Edition

The dashboard is segmented into several sections that can be selected on the top left of the browser window.

The Overview section of the dashboard shows the most important key figures and visualizations of the COVID-19 pandemic, such as the world map and a list of countries with their respective number of confirmed, recovered, deceased and active cases. A time-lapse feature with a simple slider is included to get an idea about the development of the pandemic.