The COVID-19 pandemic has many people wondering what to expect and local and federal governments alike scrambling to figure out how to respond. It is clear that we do not yet sufficiently understand how this disease spreads and how it can be contained most effectively. But there is more and more data available now that allows us to compare spread and evolution of the disease in different countries. To that end we were curious about the data provided by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU) that is used to feed their map of global cases. Specifically, we wanted to know:
We felt that insights into these questions could shed some light on the effectiveness of the various approaches tried by different governments to contain or slow the spread.
To address this, we used that data and created a more elaborate dashboard that can be found here:
The data for that dashboard will be kept up to data from the CSSE data, and hence provides additional means for data analysis. Note that the data has some clear deficiencies. For instance, the current data set seems to be missing data from the US until just recently, which reflects in unreasonably abrupt increases in the charts for the US and its states. Nevertheless, and as the data improves, we believe this tool still provides value.
We invite you to explore it and share your findings. Below are a few things we found in our own exploration worth sharing.
When we look at the death rate in regions with sufficiently many cases to where there seems to be enough data, it is striking to see how much that rate varies between different countries:
There are countries like Norway that have over 500 confirmed cases but no reported deaths, while other countries, near the bottom of that list have death rates over 3%. Comparing the US and Germany for instance, it is surprising to find a death rate that is 17 times higher in the US than in Germany. Why is that? While we certainly cannot answer this question definitely without more and better quality data, some hypotheses come to mind: Is Germany more proactive in testing for Coronavirus and is hence finding more cases that do not result in deaths? If so that would be good news as the real death rate of the virus may be lower than currently assumed by the WHO. Or is Germany perhaps not correctly diagnosing some deaths that did happen but were perhaps incorrectly not attributed to the virus? Other possible explanations include that Germany's health care system could be more effective at treating patients with the disease, or that fewer older people are getting infected, just by virtue of the types of communities that are effective.
Keeping track of this data and cross-referencing it with other data sources, and especially data coming out on the number of tests administered in these countries seems worth while in studying this pandemic.
One question on everyone's mind, of course, is whether this virus can still be contained and whether such efforts are showing any signs of success. To that extend charting the cases per country is a useful first tool.
Looking at the curvature/gradient of these charts, we immediately see that not just China seems to have been able to get the spread under control effectively, but also South Korea is showing some early signs in slowing the spread. This is encouraging.
In contrast, we see that other countries are still struggling to make any in-roads in curbing the spread, e.g., Italy, which quickly surpassed South Korea in number of cases:
We provide this dashboard in a hope to contribute to the understanding of this pandemic and we plan on adding additional statistics over time that we think could be useful to track besides the mere number of cases, e.g., 1st and 2nd derivatives of case numbers to make it easier to see how countries rank in their efforts to contain the spread. Please let us know if you have suggestions on which statistics or features to add, or if you know about other data sources we should consider integrating.