It has been some five months since the COVID-19 pandemic dawned on people's consciousness and three months since many nations went into some form of compulsory social distancing to help manage the pandemic. In this context, I thought it time to reflect on how nations have performed.
This required me to establish a benchmark for measuring success. For this I have selected four factors:
- how bad did the pandemic get at its peak in the nation (indicated by daily new deaths and daily new cases)
- how bad is the pandemic currently (indicated as aboved)
- how well have nations done in reducing the pandemic from its peak (as a proportion of that peak in daily new deaths and daily new cases)
- what is the case fatality rate for the nation (total deaths over total cases).
The population and COVID data I used for this analysis comes from the European Centre for Disease Prevention and Control.
For simplicity, I will limit my analysis to nations with a population of at least 1 million people.
To enable comparability between large and small nations, I am going to focus on cases and deaths per million population.
As I am working with noisy administrative data, I will do the analysis based on a 14-day rolling average. This irons out the tendency in many nations to under-report on weekends. It also helps reduce the impact of data spikes when nations fess up to additional deaths or cases not previously recorded.
Because the distributions of these data can have nation-states bunched around certain data points, with long tails and outliers, I have decided the group the data into quintiles (5 equal groups), and create an index score from averaging the quintile result across the seven categories:
- average daily new cases per capita at each nation's peak peak
- the most recent result for average daily new cases per capita
- the percentage decline from the peak average daily new cases per capita and now
- average daily new deaths per capita at the peak
- the most recent result for average daily new deaths per capita
- the percentage decline from the peak in average daily new deaths per capita and now
- the case fatality ratio
Before we get to the per-capita charts, let's quickly identify our top ten:
- Top 10 current cases per million population: Qatar, Bahrain, Chile, Kuwait, Peru, Armenia, Oman, Brazil, Belarus, and Panama
- Top 10 national peak cases per million population: Qatar, Bahrain, Chile, Kuwait, Peru, Spain, Ireland, Singapore, Armenia, and Oman
- Top 10 current deaths per million population: Sweden, Brazil, Peru, United Kingdom, Mexico, Chile, United States, Canada, Panama, Armenia
- Top 10 national peak deaths per million population: Belgium, Spain, France, United Kingdom, Italy, Ireland, Sweden, Netherlands, United States, Ecuador
The following charts show the per-million-population daily cases and deaths data for selected nations. I should note that as the cases data for Qatar is such an outlier, I have adjusted the y-scale in the other case charts where Qatar in not highlighted.
Which brings us to the score for each nation, reflected in the choropleth map at the top of this post:
Sweden 4.857143 Mexico 4.857143 Panama 4.714286 Brazil 4.714286 Moldova 4.714286 Peru 4.714286 Armenia 4.571429 North Macedonia 4.571429 Guatemala 4.428571 South Africa 4.428571 Canada 4.428571 Bolivia 4.428571 United States 4.428571 Chile 4.428571 United Kingdom 4.428571 Colombia 4.428571 Iran 4.285714 Oman 4.285714 Mauritania 4.285714 Ecuador 4.285714 Honduras 4.142857 Kuwait 4.142857 Saudi Arabia 4.142857 Russia 4.142857 Qatar 4.142857 Portugal 4.142857 Bahrain 4.142857 Argentina 4.000000 Romania 4.000000 Egypt 4.000000 Belgium 4.000000 Netherlands 4.000000 Dominican Republic 3.857143 Pakistan 3.857143 Azerbaijan 3.857143 Iraq 3.857143 Ireland 3.857143 Italy 3.857143 Belarus 3.857143 Puerto Rico 3.857143 France 3.857143 Gabon 3.714286 Nicaragua 3.714286 Poland 3.714286 Afghanistan 3.714286 United Arab Emirates 3.714286 Spain 3.571429 Bulgaria 3.571429 Ukraine 3.571429 Cameroon 3.571429 Denmark 3.571429 Yemen 3.571429 El Salvador 3.571429 Turkey 3.571429 Bangladesh 3.571429 Sudan 3.428571 Bosnia And Herzegovina 3.428571 Guinea Bissau 3.428571 Haiti 3.428571 Kyrgyzstan 3.428571 Estonia 3.428571 Finland 3.428571 Austria 3.428571 Germany 3.428571 Mali 3.285714 Central African Republic 3.285714 Kazakhstan 3.285714 Philippines 3.285714 Indonesia 3.285714 India 3.285714 Hungary 3.285714 Algeria 3.285714 Equatorial Guinea 3.285714 South Sudan 3.285714 Lithuania 3.285714 Israel 3.142857 Somalia 3.142857 Kenya 3.142857 Switzerland 3.142857 Czechia 3.142857 Senegal 3.000000 Albania 3.000000 Slovenia 3.000000 Liberia 3.000000 Sierra Leone 3.000000 Serbia 3.000000 Cote D'Ivoire 2.857143 Chad 2.857143 Singapore 2.857143 Eswatini 2.857143 Tajikistan 2.857143 Norway 2.714286 Nigeria 2.714286 Venezuela 2.714286 Croatia 2.714286 Libya 2.714286 Uruguay 2.714286 Kosovo 2.714286 Congo 2.714286 Latvia 2.714286 Nepal 2.714286 Guinea 2.571429 Democratic Republic Of Congo 2.571429 Greece 2.571429 Ethiopia 2.571429 Syria 2.428571 Lebanon 2.428571 Ghana 2.428571 Japan 2.428571 Malawi 2.285714 Sri Lanka 2.285714 South Korea 2.285714 Cuba 2.285714 Morocco 2.285714 Togo 2.285714 Madagascar 2.285714 Jamaica 2.142857 Georgia 2.142857 Mozambique 2.142857 Uzbekistan 2.142857 Rwanda 2.142857 Cyprus 2.142857 Malaysia 2.000000 Palestine 2.000000 Tunisia 2.000000 Trinidad And Tobago 2.000000 Costa Rica 2.000000 Angola 2.000000 New Zealand 2.000000 Niger 2.000000 Paraguay 2.000000 China 1.857143 Burkina Faso 1.857143 Zimbabwe 1.857143 Mauritius 1.857143 Slovakia 1.714286 Benin 1.571429 Botswana 1.571429 Mongolia 1.571429 Burundi 1.571429 Uganda 1.571429 Australia 1.571429 Lesotho 1.571429 Myanmar 1.428571 Zambia 1.428571 Gambia 1.428571 Thailand 1.428571 United Republic Of Tanzania 1.428571 Jordan 1.428571 Namibia 1.285714 Taiwan 1.142857 Vietnam 1.000000 Cambodia 1.000000 Laos 1.000000 Timor Leste 1.000000 Papua New Guinea 1.000000
