Covid-19: Deep-Dive into the Worldwide Data

gralovis insights private limited
28 min readFeb 12, 2021

Introduction

Covid-19 is a pandemic that has hit almost all countries across the world. None of the living generations had ever seen something that has caused such major disruptions across the world. However, not all countries have been affected equally or similarly. In this paper we will attempt to get a general understanding to a country specific understanding of the disease. We will also attempt to relate various socio-economic measures.

The intention of this paper is not to establish any cause-effect relationship. The intention of this paper is to provide a deep understanding that would remain at the back of the mind of the reader when doing any other specific study related to Covid-19. This intention is to empower the reader with a deep “general knowledge” that could be used elsewhere. The paper is divided into four sections. The first section will deep-dive into the cases. The second section will try to see association of cases with various socio-economic indicators of the countries. The third section will deep-dive into deaths. The fourth section will try to see association of deaths with socio-economic indicators of the countries.

Section 1: The Trajectory of Cases

At the start we would look at the trajectory of cases. Starting with the total world, we will drill down into continents, regions within continents and finally countries.

Since we will be doing comparisons, total cases themselves are not comparable across countries as high population countries will tend to have more cases than the low population countries. For that reason, we will use total cases per million population. This will make the data comparable across countries.

Looking at the total world graph we can see that the exponential rise is still present. Overall, close to 10 thousand per million or about 1% of the world population has been infected at the time of writing this report.
Drilling down into continents (we have clubbed Americas and Oceania into one group, but later one we will see separately in regions), we see the picture starkly different in different continents.

While Africa and Asia have far less than 1% of the population infected (about 0.2% and 0.4% respectively), Americas+Oceania and Europe have over 3% or close to 3% infected. In this section we will continue to drill down into regions and countries to figure out which are like others and which are different. After our drill down, in the next section we will try to explore reasons for same.

Trajectory of Cases in Americas+Oceania and Regional Drill-Down

This group of continents has witnessed high to exceedingly high number of cases except in Oceania.

Central America region of North America has had a little above average cases (1.1%).

The Rest of North America has had exceptionally high cases of 4.6%).
Oceania has quite low cases at 0.08%.

Trajectory of Cases in Central America and Country Drill-Down

Central America trajectory is still on the rise. This region has a little more than world average cases at 1.1%.

The countries have been a mixed bag of cases in this region. Some low (about 0.7%), some average (1% to 1.1%), some high (2.6% to 3.1%) and one very high (5.0%).

Panama has had very high cases at 5.0%. Nicaragua had very low cases at 0.09%.

Trajectory of Cases in Rest of North America and Country Drill-Down

There have been several waves that seem to be primarily driven by United States.

United States is by far the worst affected with extremely high cases leading to 5.4% of the population infected.

Three other countries have a little high level of cases (1.4% to 2.0%), but most other countries have low cases (0.5% or far less). This region is clearly skewed by United States.

Trajectory of Cases in Andean States and Country Drill-Down

Andean States is almost 2.5 times the world average with 2.5% cases.

It has average to high cases across countries.

Chile (3.1%), Columbia (3.0%), and Peru (3.0%) have quite high cases, Bolivia (1.3%) and Ecuador (1.2%) have a little above average cases, Venezuela has low cases (0.4%).

Trajectory of Cases in Rest of South America and Country Drill-Down

The rest of South America too has quite high level of cases at 3.3%. This has been skewed by Brazil (3.4%), but other countries have much lower cases.

Paraguay has above average cases at 1.4%), Suriname is on the average at 1.0%). Guyana (0.8%) and Uruguay (0.4%) have below average cases.

Trajectory of Cases in Oceania and Country Drill-Down

Oceania has had two waves but is now stable and has low cases (0.075%).

In fact, it is Australia (0.1%) and New Zealand (0.04%) that are skewing this region, else this region would have had almost negligible level of cases (0.0003% to 0.0085%) as seen in countries other than these two.

Trajectory of Cases in Europe and Regional Drill-Down

Europe is at a high level of cases at 2.9% with a trajectory on the rise.

All regions of Europe are similarly at high levels. Eastern Europe at 2.2%, Northern Europe at 2.2%, Western Europe at 3.2%, and Southern Europe at 3.6%.

Trajectory of Cases in Southern Europe and Country Drill-Down

Southern Europe has a high of 3.6% cases with a second wave in the trajectory which shows early signs of tapering.

Andorra is the worst affected with an extremely high level of 9.8%. San Marino (6.3%), Slovenia (5.1%), and Croatia (4.8%) are countries which also have quite high level of cases.

Rest of the countries have cases ranging from 2.5% to 3.6%, with Albania at 1.9%.

Trajectory of Cases in Western Europe and Country Drill-Down

Western Europe also has high cases at 3.2%.

Extremely high cases have been registered in Luxembourg at 7.1% followed by Czechia (5.9%), Belgium (5.4%), Switzerland (4.8%), Liechtenstein (4.7%), Lithuania (4.2%), and Netherlands (4.2%).

High cases are seen in France (3.9%), Austria (3.8%), Poland (3.2%), Hungary (3.2%), UK (3.1%), Slovakia (2.8%), Malta (2.7%).

Rest had above average cases ranging 1.6% to 1.9%.

Trajectory of Cases in Eastern Europe and Country Drill-Down

Eastern Europe has high cases at 2.2% and the trajectory is on the rise.

All countries have higher than global average cases. Montenegro has extremely high cases at 7.1%. All other countries have high cases but less than 5%.

Greece is the only country which is close to but higher than average at 12.6%.

Trajectory of Cases in Northern Europe and Country Drill-Down

Like Eastern Europe, Northern Europe has high cases at 2.2% and the trajectory is on the rise.

Sweden at 3.6% is the worst affected in the region. Denmark has a high of 2.4%.

Iceland is above average at 1.7%.

Norway at 0.8% and Finland at 0.6% are the lower-than-average cases in the region.

Trajectory of Cases in Asia and Regional Drill-Down

Asia has been a mix of regions with low to medium number of cases with a below average level of 0.4%.

Central Asia (0.5%), East Asia (0.02%), Indian Subcontinent (0.6%), and South-East Asia (0.2%) had low cases. Arabian Peninsula (1.8%) and Fertile Crescent (1.8%) has had more than average cases. Only South Caucasus which is close to Europe has had high cases at 3.3%.

Trajectory of Cases in South Caucasus and Country Drill-Down

South Caucasus region has high level of cases at 3.3% with a trajectory on the rise.

Armenia (5.2%) and Georgia (5.2%) are at extremely high level of cases.

Azerbaijan is at a high of 2.0%.

Trajectory of Cases in Fertile Crescent and Country Drill-Down

The Fertile Crescent region has had above average cases (1.8%) with a trajectory that is recently showing early signs of tapering.

All countries except Syria (0.06%) have high cases. The worst affected is Israel with 4.4% infected. Next set of three countries with 2.3% to 2.7% infections are Jordon, Lebanon, and Palestine.

Iran and Iraq have a little more than average cases of around 1.4%.

Trajectory of Cases in Arabian Peninsula and Country Drill-Down

The trajectory of Arabian Peninsula is now stabilizing. Overall, it has above average cases at 1.8%.

Only Saudi Arabia at 1.0% is at almost the world average.

Kuwait (3.5%), Oman (2.5%), and UAE (2.0%) have high cases

Bahrain (5.3%) and Qatar (4.9%) have quite high levels of infections.

Trajectory of Cases in Central Asia and Country Drill-Down

The trajectory in Central Asia has been tapering. Overall, it has less than world average cases at 0.5%.

Kazakhstan (1.0%) and Kyrgyzstan (1.2%) have a little above world average level of cases.

Tajikistan (0.1%) and Uzbekistan (0.2%) have much below world average level of cases.

Trajectory of Cases in Indian Subcontinent and Country Drill-Down

The Indian Subcontinent has overall below average cases at 0.6% and the trajectory is tapering.

The worst affected is Maldives with a high of 2.5% cases.

India (0.7%) and Nepal (0.9%) have a little below average level of cases.

All other countries have low level of cases (0.1% to 0.3%) with Bhutan at a very low of 0.06%.

Trajectory of Cases in South-East Asia and Country Drill-Down

Overall South-East Asia has low level of cases at 0.2%.

Singapore is relatively higher in the region with close to average cases of 1.0%.

All other countries have low to exceptionally low to almost negligible cases of 0.4% or less.

Trajectory of Cases in East Asia and Country Drill-Down

East Asia is showing a second wave upswing now. However, the region has maintained quite low level of cases overall at 0.2%.

If we drill into country level, Japan (0.16%) and South Korea (0.1%) have relatively higher cases but still at quite a low level compared to world average.

Mongolia is still at a much lower level (0.03%). China (0.007%) and Taiwan (0.003%) have almost negligible levels. China is a surprise!

Trajectory of Cases in Africa and Regional Drill-Down

As we have seen earlier, Africa is the Continent with lowest cases per million. The trajectory shows two distinct waves but still in control considering comparisons with other regions.

Out of the five regions of Africa, it is Southern Africa that has the most infections of over 1.4%.
North Africa is the next highest region in infections.

The other three regions — Central Africa, East Africa, and West Africa had exceptionally low cases per million.

Trajectory of Cases in Southern Africa and Country Drill-Down

Southern Africa has had two waves and cases are on the rise with a high infection rate of 1.4%.

South Africa shows quite high levels of infections of 1.6%, while other countries have lower than world average (less than 1%).

Lesotho is the only country in this region that has maintained quite low levels.

Trajectory of Cases in North Africa and Country Drill-Down

Although overall North Africa has below average cases, drilling into country level we see that it is because of Algeria and Egypt that have been able to keep the numbers in control, while Libya, Morocco, and Tunisia have had levels of infections above the global average of 1% to 1.4%.

Trajectory of Cases in East Africa and Country Drill-Down

All countries of Central Africa registered much less than the global level of cases per million.

Djibouti had relatively much higher cases (although still half the global average) at about 0.6% than all other countries of the region.

Trajectory of Cases in West Africa and Country Drill-Down

West Africa also has had two waves and cases are on the rise. Overall, this region has had quite low cases (0.06%).

The only outlier in this region is Cape Verde that has exceptionally high level of cases of 2.1%. All the other countries have had low to very low cases (negligible to 0.3%).

Trajectory of Cases in Central Africa and Country Drill-Down

All countries of Central Africa registered much less than the global level of cases per million. Additionally, the trajectory further appears to slow-down.

Apart from the three countries of Equatorial Guinea, Gabon, and Sao Tome and Principe, all others registered extremely low cases.

Summary of Section 1

There are particularly two things we notice.

The first thing we notice is that there is some sort of regional clusters that are playing a role in number of cases per millon. Some regions as a whole show high cases across countries, while some regions show low cases across countries. However, there are some regions with a mixed bag.

Southern Europe, Eastern Europe, and Western Europe across countries have above average to high cases. Countries of South Caucasus in Asia, which is close to Europe have above average to high cases. Arabian Peninsula countries have above average to high cases. With the exception of Venezuela the countries of Andean States of South America too have high cases. Similarly, with the exception of Syria the countries of Fertile Crescent too have above average to high cases. This makes 7 out of 21 regions in the distinct group of countries generally having above average cases.

Oceania has quite low cases across countries. With the exception of Maldives, the Indian Subcontinent countries have below average to low cases. With the exception of Singapore which has average number of cases, South East Asia countries have low to quite low cases. East Asia countries have extremely low cases. With the exception of South Africa, the countries of Southern Africa have below average to low cases. East Africa countries have low to extremely low level of cases. With the exception of Cape Verde the countries of West Africa have low to very low level of cases. Central Africa countries have low to very low cases. This makes 8 out of 21 regions having below average to low level of cases.

The remaining 6 regions are a mixed bag. Which also means that 15 out of 21 regions are not a mixed bag but with some exceptions.

The second thing we notice is that as we move from west to east, the level of cases gradually decline. We see this very distinctly as we move through west to east of Europe and then further east from Middle East to Indian Subcontinent to South-East Asia to East Asia and then further east to Oceania. The pattern generally declines very gradually.

In the earlier section we looked at trajectory and current level of cases across continents, regions, and countries. This has given us an understanding of geographical patterns which we could summarize. In this section we will look at various socio-economic indicators and related variables and try to establish if any kind of association exists or not with the level of cases per million.

At the outset, we would like to remind the reader that we are not trying to establish any causation. The good old saying should be remembered — “Correlation does not imply causation.” In this section too we are trying to draw out pattern that may exist and add to our “general knowledge” of this pandemic.

The charts are on log-transformed data to ensure a better spread. We have a trend-line and the shaded area of 95% confidence level of the association. This shaded area is something we should be looking into.

Section 2: How Cases are Associated with Various Socio-Economic Indicators?

Variable: Total Tests per Thousand

In the list of variables that we have considered, total tests per thousand in a country appears to have the strongest association.

“When you test, you have a case,” was stated by US President Donald Trump, implying higher rate of testing would lead to higher rate of cases.
Though it may not be entirely false, this does not seem to be the case in the Americas+Oceania. Nor is it in Europe.

However, in Africa and Asia, there is a significant association.

Variable: Human Development Index

The next variable is Human Development Index. The higher the HDI the more is the infection rate in the country.

Overall, the 95% shaded area suggests a significant association.

Moreover, we see this association in all continents except Europe where there is no association to this variable. Also, the European countries have a lesser variance in HDI.

Variable: GDP per Capita

The next variable is GDP per Capita. The higher the GDP per Capita, the more is the infection rate.

The association is significant overall.

The association is strongest in Africa and does not exist in Europe.

Variable: Median Age

The next variable is median age. The higher the median age the more is the infection rate in the country.

Overall, there is a significant association as we see in the World chart. However, the strength diminishes as we drill into continents. Africa still shows the highest level of association, while Europe has almost no association at all.

Variable: Extreme Poverty

Share of the population living in extreme poverty as per World Bank has a reverse association overall. The higher the share, the lesser is the infection rate.

We see this association in Africa, but it diminishes in Americas+Oceania and Asia. Europe shows no association at all.

Variable: Life Expectancy

The next variable is Life Expectancy. The higher the life expectancy the more is the infection rate in the country.

Overall, the 95% shaded area suggests a significant association.

Moreover, we see this association in all continents except Europe where the association is almost absent. Also, the European countries have a lesser variance in life expectancy.

Variable: Aged 65 plus

The next variable is percent of population aged 65 or above. The higher the aged proportion the more is the infection rate in the country.

The association is less significant than the previous variables we saw (as the 95% shaded area is wider).

However, when we drill down to continents, the association is almost absent in all continents except Africa. Europe which we know has higher infections and also has higher aged population was causing the (illusion of this) association at the global level.

Variable: Female Smokers

The next variable is percentage of female smokers. The higher the percentage of female smokers, the more is the infection rate in the country.

But when we drill into continents, only Europe shows a good level of strength in association while in the other three continents, the association almost vanishes.

Variable: Positive Rate

Share of Covid-19 tests that are positive have some association with infection rate.

Generally, the more tests are done, the more cases are found but expected at a diminishing rate. This in turn leads to better containment of spread.

All continents show some degree of association with this.

Variable: Handwashing Facilities

The next variable is share of the population with basic handwashing facilities on premises. The more the percent of population that has this access, the more the infection rate.

There is some association in Africa and Americas+Oceania, but far more significant is the association in Asia. Most European countries did not have this data available.

Variable: Cardiovascular Death Rate

Cardiovascular Death Rate has a negative association with cases per million. The more the death rate, the lower is the infection rate.

However, when we drill down to continents, we see that this association is completely absent in Africa, Asia, and Europe.

But in America+Osceania the association is a strong negative one.

Variable: Diabetes Prevalence

Percent of adult population with diabetes has almost no association with infection rate at the global level.

However, when we drill down we see America+Osceania having a strong negative association while Asia having a strong positive association.
The other two continents of Africa and Europe do not have any association.

Variable: Population Density

The last variable we examine is the population density. It too does not have any association with the infection rate.

Drilling into continents we see some weak association, but these are not significant and can be considers as no association in each of the continents too.

Summary of Section 2

Comparing socio-economic indicators with cases per million we notice a few things.

There is some association, but never strong, with many indicators. The association is not consistent across continents. Each indicator has less variance in Europe. Europe also exhibits no association of cases per million with many indicators.

Most important thing we notice is that contrary to expectations, the more well-off countries (as per the various indicators), tend to have higher cases per million.

Section 3: The Death Curve

The main reason why Covid-19 has caused disruptions across the world is its relatively high death rate. As today it stands, the world average is more than two percent. This rate coupled with high cases makes the number of deaths a large number.

Although most statistics being used is deaths per million population, but this is misleading to compare across countries as those countries with a higher cases per million population will tend to have higher deaths per million population. So, studying this variable will not lead to any more understanding than what we have already see in the first section.

Therefore, we need to study deaths independent of cases. For this reason, in this section we will examine deaths as deaths per thousand cases.

Overall, the death rate peaked in May 2020 with over 7% and has subsequently declined to the level of 2.2%.

Across continents it is not vey different in Americas+Osceania (2.5%), Africa(2.4%), and Europe (2.3%). However, the rate in Asia is much lower at 1.6%.

The Death Curve in Americas+Oceania and Regional Drill-Down

The worst affected is Central America region of North America at 6.6%.

Lowest is Rest of North America at 1.8%.

The Death Curve in Central America and Country Drill-Down

The death rate in Central America peaked in June-July 2020 to almost a high of 10%. Since then it has been slowly declining and stands at a high of 6.6%.

The worst affected is Mexico at 8.9%. This is the country which is skewing the entire region.

Other countries of the region have a death rate of 3.5% to a low of 1.3%.

The Death Curve in Rest of North America and Country Drill-Down

The rest of North America had two peaks — one early in March 2020 at close to 8% but it quickly subsided to below 2%. Then it rose again and peaked in May-June 2020 to over 6%. Since the it has been gradually declining and is now at 1.8%.

The country level death rate ranges from 3.3% to a low of 1.3%.

The Death Curve in Andean States and Country Drill-Down

Andean States had lower death rates in the initial stages which rose to above 3.5% and is now at 3.1% wit the curve showing a slight declining trend.

The countries in this region have varied death rates with Ecuador (6.8%) and Bolivia (6.0%) on the high side. Peru not quite high at 3.7%. At the above average level are Chile (2.8%), Argentina (2.7%), Columbia (2.7%). Venezuela is at the low rate of 0.9%.

The Death Curve in Rest of South America and Country Drill-Down

Rest of South America peaked in May 2020 close to 7%, but gradually has come down to 2.6%. The trend is still on a slight decline.

Uruguay has the lowest rate of the region at 0.9%. All other ranged between 2.1% and 2.6%.

The Death Curve in Oceania and Country Drill-Down

Oceania is on the third peak and plateauing. However, the peaks were never very high and have been a little over 3.5% or below. The most recent peak was in September 2020 above 3% and now has come down a little to 3.0%.

Fiji (4.3%) and Australia (3.2%) are the countries with a higher death rate. While Papua New Guinea and New Zealand both are at a low of 1.2%.

The Death Curve in Africa and Regional Drill-Down

The death rate in Africa peaked between April-May 2020. Subsequently it came down and has been stable since Sep 2020. Currently it stands at 2.4% which might be its long-tern stable rate.

North Africa and Southern Africa are at a death rate of 2.6%, Central Africa and East Africa at 1.9%, and West Africa is lowest in the continent at 1.4%.

The Death Curve in North Africa and Country Drill-Down

North Africa peaked in April 2020 with a high of close to 10% and then quickly came down to 4% and then gradually to 2.6% where is stands now.

Egypt is the worst affected at 5.6%. Tunisia (3.5%) and Algeria (2.8%) are above average. Morocco (1.7%) and Libya (1.4%) are below average.

The Death Curve in Southern Africa and Country Drill-Down

Southern Africa had multiple peaks with each peak higher than the previous. However, none of the peaks were high. It currently stands at 2.6%.

South Africa is above average at 2.7%. Close to average at 1.9% are Lesotho and Eswatini. Namibia is at a low of 0.9% and Botswana quite low at 0.3%.

The Death Curve in Central Africa and Country Drill-Down

Central Africa had multiple peaks during April-May 2020 and touched a high of above 6%. It now stands at a level little below global average at 1.9% and has been stable since June 2020.

Chad is an outlier country with a high of 5.4%. Other countries are at above to below average between 2.4% and 1.3%. Gabon is the lowest in the region with a low level of 0.7%.

The Death Curve in East Africa and Country Drill-Down

There was an initial outlier high rate in March, so this plot starts from April 2020. East Africa peaked in May 2020 close to 3.2% and has gradually come down to now at 1.9%.

Only Sudan is at extremely high at 6.3%. Tanzania is at a high of 4.1%. Three of seventeen countries have above average between 3.0% to 2.6%. That’s five with above average to high.

The rest 12 of 17 have below average to low between 2.0% to 0.3%.

The Death Curve in West Africa and Country Drill-Down

West Africa peaked in April 2020 at above 3% and has now come down to a below average level of 1.4%.

The countries in this region are a mix of high to average to low. The range of death rate is the highest of 4.7% in Liberia to a low of 0.6% in Ghana, Cote d’Ivoire, and Guinea.

The Death Curve in Europe and Regional Drill-Down

Europe peaked in May 2020 with quite high almost 10% death rate. Subsequently it has come down and has been stable at 2.3% since a couple of months.

Southern Europe registered 2.9%, Western Europe 2.3%, Eastern Europe 1.9%, and Northern Europe 1.7%.

The Death Curve in Southern Europe and Country Drill-Down

Southern Europe had a long peak during April-June 2020 of over 12%. Subsequently is has come down and recently appears to plateau at 2.9%.

At above average are Italy 3.5%, Bosnia and Herzegovina 3.5%, Spain 2.7%, San Marino 2.6%, Kosovo 2.6%.

At close to average are Slovenia 2.2%, Albania 2.1%.

At below average are Croatia 1.7%, Portugal 1.6%, Andorra 1.1%.

The Death Curve in Western Europe and Country Drill-Down

Western Europe had a long peak during April-Jun 2020. It went up to a high of over 11%. Subsequently it has come down and has stabilized in last two months at 2.3%.

United Kingdom is the highest hit at 3.3%. Four of nineteen other countries were above average between 3.0% to 2.4%. Poland close to average at 2.1%. Eight of nineteen other countries below average between 1.8% to 1.4%. And five of nineteen low between 1.1% to 0.5%.

The Death Curve in Eastern Europe and Country Drill-Down

Eastern Europe peaked in April 2020 but a relatively low peak of 2.5%. Subsequently it came down, up, down, and up again, at is now at 1.9% with the curve showing a bit rise.

Bulgaria (3.5%) Greece (3.2%), North Macedonia (3.0%), Romania (2.4%) are the countries with death rate higher than global average.

Moldova (2.0), Russia (1.8%), Ukraine (1.7%), Montenegro (1.4%) are countries with below average death rate.

Low rates are in Serbia (0.9), Belarus (0.8%), Cyprus (0.5%).

The Death Curve in Northern Europe and Country Drill-Down

Northern Europe had a slightly long peak in April 2020 of about 8.5%. Subsequently it has come down to 1.7% and appears further declining.

Sweden is the only country with average rate at 2.2%.

Other countries show below average or low rates with Finland at 1.5%, Norway at 0.9%, Denmark at 0.8%, and Iceland at 0.5%.

The Death Curve in Asia and Regional Drill-Down

The death rate in Asia peaked in April 2020 around 4.5%. Subsequently it has been coming down had stabilized in October 2020 but again came down in December 2020 and now stands at 1.6%. This is the lowest rate across continents and the curve suggests that there are chances that it may go down further.

Regions range for above average of 2.4% in East Asia to a low of 0.9% in Arabian Peninsula.

The Death Curve in East Asia and Country Drill-Down

East Asia had a long peak during May-July 2020 of over 5%. Subsequently it has come down and continues to decline at 2.4%.

China is at a high of 5.0%.

All other countries are below average with Japan at 1.4%, South Korea at 1.5%, and Taiwan at 0.9%.

The Death Curve in South-East Asia and Country Drill-Down

South-East Asia peaked in April 2020 over 4% and quickly came down and now appears stabilizing at 2.3%.

Indonesia (3.0%) and Vietnam (2.5%) are at above average.

Myanmar (2.1%), Brunei (2.0%), Philippines (1.9%) are at below average.

Thailand (1.0%), Malaysia (0.5%), Singapore (<0.05%) are at low to extremely low levels.

The Death Curve in Fertile Crescent and Country Drill-Down

There was an initial outlier high rate in February, so this plot starts from March 2020. Fertile Crescent peaked in March-April 2020 over 7%, the came sharply down during April 2020 and then has gradually come down to 3% and with a recent dip, is now at 2.0%.

Syria is quite high at 6.0%. Iran is at a high of 4.6%.

Iraq at average of 2.2%.

All others at below average between 1.3% to 0.8%.

The Death Curve in Indian Subcontinent and Country Drill-Down

Indian Subcontinent peaked in April-May 2020 with a low peak close to 3%. It has subsequently come down and is now stabilizing at 1.5%.

Afghanistan is the only country with a high rate of 4.2%.

Pakistan is close to average at 2.1%.

Bangladesh and India both below average at 1.5%.

Nepal (0.7%), Sri Lanka (0.5%), Maldives (0.4%) witness low rates.

The Death Curve in Central Asia and Country Drill-Down

Central Asia has had quite low peaks first in April 2020 of about 1% and then after some decline another peak in August-September 2020 about 1.6%. This has subsequently come down slightly and stabilizing at 1.3%.

All countries have below average to low rates between 1.9% and 0.7%.

The Death Curve in South Caucasus and Country Drill-Down

South Caucasus first peaked in March 2020 at over 2% but quickly came down and rose again with another loner peak during August-September 2020 of around 1.7%. Subsequently, it has come down and appear stabilizing at 1.2%.

All three countries have below average rates between 1.7% and 1.0%.

The Death Curve in Arabian Peninsula and Country Drill-Down

Arabian Peninsula had quite a low initial peak of below 0.8%. Then it came down and has risen again to a new peak of 0.9% which appears stabilizing.

Saudi Arabia (1.7%) and Oman (1.2) are at below average rates.

All other countries are at low rates of 0.6% to 0.2%.

Summary of Section 3

What we notice is that almost all regions had peaks around May 2020. Some regions had quite high peaks and some low. But irrespective of the level of peak all regions and have current rates under 3% except Central America.

There are 8 countries with quite high current rates above 5%, 18 countries with high current rates above 3%, 109 countries with medium rates between 1% and 3%, and 37 countries with low rates below 1%. So, there are many more countries on medium to lower side.

Section 4: How Deaths are Associated with Various Socio-Economic Indicators?

Like we did for cases per million, similarly we will examine deaths with various indicators in this section.

Variable: Population Density

There is quite weak to almost absent association of death rate with the population density.

We see this pattern across continents, except Asia where we there is indeed a negative association. The higher the density the lower is the death rate.

Variable: Positive Rate

There is quite weak to almost absent association of death rate with positive rate (proportion of tests that come Covid-19 positive).

Asia shows flat indicating no association. Africa too has almost no association. However, there is some degree of positive association in Americas+Osceania and Europe.

Variable: GDP per Capita

There is quite weak to almost absent association of death rate with per Capita GDP.

Africa shows flat indicating no association. Americas+Osceania and Europe too have almost no association.

However, there is a clear negative association in Asia, but that too seems to be the effect of the low rates of Arabian Peninsula that has higher per Capita GDP.

Variable: Total Cases per Million

Would cases themselves affect death? Overall, there is almost no association.

However, different continents show some weak association but not consistently one-sided.

While Africa and Asia show weak negative association meaning more case-rates lead to lower death-rates, the West shows weak positive association.

Variable: Human Development Index

There is quite weak to almost absent association of death rate with Human Development Index (HDI).

Africa and Americas+Oceania show flat indicating no association. Europe is also almost flat.

However, there is a clear negative association in Asia, but that too seems to be the effect of the low rates of Arabian Peninsula that has higher HDI.

Summary of Section 4

Unlike cases per million that had some degree of association with many socio-economic indicators, deaths per 1000 cases does not have any significant association with any socio-economic indicator.

Even at the continent level where Asia shows some association, it too is primarily doe to the Arabian Peninsula cluster of countries.

Final Takeouts

With this we now have a global, continental, regional, and country level picture of the pandemic. It is a mixed story with some patterns that are clearly visible.

Finally, we can make the following four points:

  • Cases per million population are quite well explained by the regional cluster the country is in. Regions tend to behave similarly.
  • There is some association of cases per million with socio-economic indicators but is weaker than the regional association and affluence has tended to have led to more cases.
  • Death rates have peaked around April 2020 to high levels in many cases, but most countries now have death rates in control.
  • Death rates have no relationship with socio-economic indicators.

Credits

The source of data for this report is Our World in Data. Their repository on github has the complete data used here and is distributed by them under the “Creative Commons” license which allows free use as long as the source is duly credited (as being done here).

[Hasell, J., Mathieu, E., Beltekian, D. et al. A cross-country database of COVID-19 testing. Sci Data 7, 345 (2020). https://doi.org/10.1038/s41597-020-00688-8]

This report has been prepared by gralovis insights private limited, Mumbai — 400078, India

Originally published at http://gralovis.com.

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