COVID-19: Months into Minutes

​There are some really useful maps and charts that help us to make sense of the patterns of coronavirus occurrence and severity. The most familiar are variations on the theme used by the WHO in their daily Situation Reports. There is also the excellent COVID-19 Dashboard from the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU), and I love the COVID-19 GIFs from World Mapper. The map below, used in an excellent Newsweek article, is representative of the typical maps we see every day. They provide useful summaries but do not capture the patterns as they unfold over time. 

Typical map of COVID-19 cases which exaggerates levels in large countries by failing to take numbers of people into account.

However, I wanted a one-stop shop - something that represented the daily progress of the pandemic over the planet, but I could not find anything that fitted the bill. The WHO maps could not, because they have used different scales throughout the infestation. They have also represented totals in terms of numbers per country rather than incidences per capita. This can exaggerate the relative severity of the situation in large and/or populous countries (notably India and Russia). This is a bit like saying India with a total GDP of $US2,800 billion is a richer country than Ireland whose GDP is $US381 billion.

So I decided to make the charts I was looking for. I also added a ‘thermometer’ to keep track of seven-day mortality as a way of gauging the effectiveness of disease management efforts at the global scale. Some people have asked why the red column on the left sometimes go down. That's because it represents the total numbers of deaths from COVID-19 during the previous seven days. When this figure drops consistently it will show us that we are really getting on top of the pandemic at the global scale.

I have used reported deaths rather than incidences as death represents the ultimate hard endpoint, and the reported incidences data strongly reflects the intensity of testing. At the time of writing (mid-April 2020) Germany, for example, has a higher number of COVID-19 cases than UK but a lower level of mortality. All this being said, it needs to be recognised that there are still great imperfections in the data on causes of death, as countries vary hugely in their detection and reporting capacity.

​Here is my first offering. 

​Below are a few of my take home observations based on this time series.

• January and February were ‘lost months’ for early COVID-19 action in Europe and USA, when decision-makers may have been lulled into a false sense of security by the (predictable) slow growth in cases in the early phase of exponential growth.
• There appears to be a relationship between climate and COVID-19 severity, with both warmer and cooler parts of the world having relatively lower mortality – the ‘viral Goldilocks effect.’ However, the climate-mortality link is far from proven, and other factors also come into play. Economic development levels appear to be important if we compare the relatively higher mortality figures of Australia and some South American countries with those for many parts of sub-Saharan Africa. Higher levels of economic development may be associated with other factors such as increased travel and more hours spent in air conditioned environments.
• At the time of writing (13 April), COVID-19 deaths are rising globally at an alarming rate, and we will need to maintain our individual and collective efforts if we are to minimise future mortality increases.

 ​I will update these videos every month. Here is the second offering. In addition to charting the trajectory of the pandemic, I ​explores some of the possible reasons for the observed patterns - climate/UV, smoking, air pollution, mobility patterns, age distribution, management practices, and dubious data.

Although not doing everything I want, the best mapping resource I have found for COVID-19 and a variety of other topics is from Our World in Data. With thousands of free, open access and open source  charts covering a range of topics including health, education, and the environment, it is a goldmine. They present the COVID-19 data in useful and interactive ways not seen on other websites. 

All free: open access and open source. An example chart is shown below.