News and fake news abound about which countries have done better in identifying and mitigating COVID-19, the efficacy of testing regimes and how nations can recover over time.
This article presents latest data on COVID-19, focussing on the 25 nations having the highest number of total cases of COVID-19 (comprising active cases, recovery and deaths), which we have calculated on a per capita basis, aligning this with other key indicators including the type of political system they have to understand whether particular systems are more adept at addressing the pandemic.
COVID -19 by the numbers
Cases per capita
Cases per Land area (Square Km)
Sources. Author calculations and interpretations drawn from Euronews https://www.euronews.com/covid-19-coronavirus-breakdown-of-deaths-and-infections-worldwide data as at 19 May; worldometer https://www.worldometers.info/world-population/population-by-country/ and Economist Democracy Index 2019 https://www.eiu.com/topic/democracy-indexCOVID -19 by the numbers
These numbers, as of May 19 2020, present some important and interesting findings. Recognising that the virus has hit different parts of the world at different times and that rates of testing and reporting vary considerably across nations, it is interesting that most of the “top” 25 nations are in the more developed part of the world. This is consistent with a recent article in QRIUS that highlighted that ignoring the threat, sending mixed messages, insufficient testing and cutting of investment in health are key factors. https://qrius.com/covid-19-has-blown-away-the-myth-about-first-and-third-world-competence/.
To these we could add complacency and an unwillingness to halt economic activity (which gives rise to these countries developed status). Further, of interest is the relative absence of Asian economies from the most affected list. Early and significant interventions were key to this result. Of the Asian countries that are on the list, Pakistan, India and China appear at the tail end of the 25 most affected. African countries are not in the list either, although the virus is starting to be felt.
Secondly, we analysed the cases on a land area basis to try and understand whether there is any greater propensity for more cases in smaller geographical areas, a “COVID-19 Density” calculation if you wish. One would expect close proximity to be a trigger for community transmission of the virus. There is a faint relationship, when also taking into account rates of urbanisation. For example, Qatar, Belgium and Netherlands have urbanisation rates well above 90%, and have the highest rates of COVID-19 on a square kilometre basis. However, the pattern is not overall especially pronounced and care needs to be taken. This is because the area is a national measure, and does not pick up sub-national concentrations of COVID-19. For example, China has had a very localised incidence of the virus e.g Wuhan, rather than it being more widespread across the country, which may account for its low COVID-19 density when measured against national area benchmark.
The other key feature to note is that with some notable exceptions (China, Switzerland, Spain and Turkey and Iran), recovery rates are relatively low. When also taking into account death rates, it suggests that there is still a very significant proportion of active cases. This means that getting on top of the pandemic is still largely elusive and time sensitive. Countries which were affected early e.g China and Iran are now on the path to recovery. This reinforces the need for testing, early identification, warning signals and preparedness, and also points to the clear need for the now agreed to global inquiry, which should put a great deal of emphasis on information sharing, open discovery and widespread dissemination of testing and treatments when they become available.
Finally, we map the incidence of COVID 19 against types of political system, as developed by the Economist, which classifies political systems according to Full Democracy (respect for political freedoms, free and fair elections, strong civil liberties, strong institutions e.g independent judiciary and independent media); Flawed Democracy (free and fair elections but with low levels of political participation, governance problems and infringements on media freedom), Hybrid (election irregularities, widespread corruption, Government pressure on opposition parties, and weaker rule of law and civil society and poor political participation) and Authoritarian ( dictatorships or elections if they occur are not free and fair, state owned media often aligned with the ruling class, censorship and repression of criticism of Government and lack of judicial independence). Specific criteria to classify nations are: electoral process and pluralism; functioning of Government; political participation; political culture; and civil liberties.
Nine out of 25 of the world’s highest cases of COVID-19 by country are full democracies and a further eight are flawed democracies. Six countries are authoritarian while two are hybrid cases. Therefore, 17 countries out of the 25 most affected in the world are democratic. Disturbingly, it would appear (and noting this is correlation not causality), being a democracy with all its attendant freedoms does not necessarily make for better COVID-19 outcomes. There could be any number of explanation for this but potentially an inability to mobilise resources quickly to deal with the problem, multiple interest groups to consider and absence of consensus could be key.
Of course, there is far more to play out with COVID-19 including the possibility of a pronounced “second wave”. At this stage, with the exception of some, the response of many countries in dealing with the crisis leaves a lot to be desired.
Dr Anand Kulkarni
The views expressed here are the author’s entirely.
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