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Correlation between wealthy countries and COVID-19 mortality rate

Linking a country's HDI with its COVID-19 mortality rate

Investigation title: Could there have been a correlation between very rich countries and COVID-19 mortality rate?

Investigation period: December 2019- November 2020 (Approx. 1 year)


The World Health Organisation (WHO) were first alerted about coronavirus, on the 31st December 2019, by a lot of pneumonia cases in Wuhan, China which have a population of 11 million. Furthermore, by 15th January 2020 there were precisely 289 cases recorded in countries such as: Thailand, Japan, S.Korea and other places in China. And of the original cases there were 6 deaths, 51 severe cases - 12 of which were in critical condition. Meanwhile, the virus responsible for the cases was isolated and its genome mapped and was shared on 12th January.               

HDI represents the measurement of development. This is a composite of Gross National Income (GNI) per capita, mean years of education and life expectancy at birth to measure the development of a country. It is calculated between a scale of 0 (least developed) to 1 (most developed) and all its values are to 3 significant figures. HDI values of 2019 and countries of HDI greater than 0.800 were used, as these are all regarded as very high HDI countries so were in the scope of this investigation. Therefore, this aimed to determine the impact of human development on the number of mortalities caused by SARS-CoV-2; where human development is measured by HDI, and the number of mortalities per hundred thousand from December 2019 to November 2020.


Stratified sampling produced 12 countries, in descending order of HDI value:

-        Australia, Netherlands, UK, Austria, Spain, Estonia, UAE, Portugal, Bahrain, Kazakhstan, Romania, Malaysia


See Table 4.


See Chart 2.

r= 0.321 (3 s.f.) – Pearson’s test

∴ There is a moderate positive linear correlation between HDI and mortality rate due to SARS-CoV-2 per 100,000.

Further stats testing- Spearman’s Rank

∑D^2 = 216

n = 12

Rs = 1 - (6 ∑D^2 )/ n(n^2 – n)

= 1 - (6 x 216) 1584

= 0.182 (3 d.p.)

Rs = 0.245 < Critical Value (0.0.587591)

∴ There is no correlation between HDI and mortality rate due to coronavirus per 100,000.


The null hypothesis was accepted: there is no correlation between a country’s HDI and its mortality rate due to SARS-CoV-2.

A biogeographical reason for this is that the more developed countries (such as those in my investigation for example the UK) have a higher level of immigration from latitudes closer to the equator therefore there is a section of their society with increased susceptibility to SARS-CoV-2 due to vitamin D deficiency. It is known that low vitamin D levels have a negative impact on immune function and that low vitamin D levels are common in the immigrant population.

Therefore, it is likely that there is a link between vitamin D deficiency and mortality rate per 100,000, however this could be overstated due to confounding factors such as socioeconomic status, residence and employment. This would explain why countries at higher latitudes like the Netherlands have higher mortality rates per 100,000 (41.80) which is the 3rd highest in this investigation.

Another explanation for this non-correlation could be that the less developed countries could be more used to dealing with a pandemic or stress on a healthcare system due to previous experience. For example, after the SARS outbreak, many countries decided to prepare in case of a pandemic, however some large HDI countries such as the UK chose not to and even ignored other warnings on the effect of a pandemic (like the exercise signs simulation).

Moreover, studies have shown that as a very high HDI country becomes more developed its healthcare system continues to develop until it reaches a peak where its effectiveness is undermined by economic benefit or interest. This would explain why the UK had a death rate of 68.00 per 100,000 and a total death count of over 45,000 (as of December 2020).


Since there is no correlation between a country’s HDI index and its mortality rate of COVID-19, this may apply to other diseases that became pandemics such as 1918’s Spanish Flu, or more recent ones like the SARS outbreak in the early 21st century.

As for tropical diseases (malaria, dengue, chikungunya and others) and other illnesses such as the common cold and the flu, these diseases present in only certain geographies. This means that the countries with these ailments will be of a similar HDI and economical status; therefore there would be a correlation between a country’s HDI index and its mortality rate of these diseases, to a certain extent.

Investigation conducted and written by Roshan Gill

Tables, charts, stats and calculations by Roshan Gill

This summary by Manisha Halkhoree

‘Implications’ section by Manisha Halkhoree

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