Globalization and the World-wide Progress of the Covid-19 Pandemic: Early-2020 to mid-2022

Covid-19 is widely considered to be related to the recent trends in globalization. Basically, viruses can hitch a ride on people, and the things that they trade, to rapidly spread around the world. This seems entirely logical, though it is always good to examine the evidence, and see how our intuitions on these matters stand up to reality.

In order to look at this, I did some simple correlations and regressions between measures of globalization and measures of Covid-19 intensity, by country, during the duration of the pandemic, from early 2020 to mid-2022.

Globalization Measures

Globalization can mean many things to many people, so how can it be quantified and measured? It turns out that there is a lot of research on the subject and a number of globalization indices have been worked out. For this purpose I will use a series of measures created by the reputable KOF Swiss Economic Institute. Here is a brief explanation of these globalization measures, as stated on their website:

“Economic globalization is composed of trade globalization and financial globalization, of which each gets a weight of 50 percent. Social globalization consists of personal contact, information flows and cultural proximity where each contributes one third. Economic, social and political globalization are aggregated to the Globalization Index using again equal weights. The overall KOF Globalization Index is calculated as the average of the de facto and the de jure Globalization Index.”

The graphs and correlation matrix below show how well these measures interact with each other, when calculated from a database of about 200 countries (each dot in the graphs corresponds to the globalization measures for a particular country). As you can see from the graphs, these measures appear to have quite a strong linear relationships (when a country is high on one variable, it is generally high on the other). The relationships between Overall Globalization, Social Globalization and Economic Globalization are especially strong, as seen by how the points tend to fall on a more or less straight lines for the relevant graphs. Political Globalization is not as strongly related, which would seem to indicate that it is measuring a somewhat different underlying phenomenon than the others.

Relationship Between Globalization Variables

In addition, they have quite high correlation coefficients. Note that a perfect positive correlation is equal to 1.00 and a perfect negative correlation is equal to -1.00, while a correlation of 0.00 indicates no linear relationship at all. Intermediate values indicate intermediate relationships.

The table of p-values indicate how likely this result would be, based on chance alone. Low p-values mean that the result is very unlikely to be a chance occurrence. P-values of less than 0.05 are conventionally considered “low enough” to provide strong evidence of a true relationship, with numbers lower than 0.01 indicating very strong evidence.

Globalization Indices Correlations

I should note that in the following analysis of the relationship between globalization and Covid-19, the globalization indices do not change over the time period of the data being analyzed. So, they measure globalization tendencies in countries at the start of the pandemic. That said, it is likely that these measures will be consistent over time, especially when comparing countries against each other – i.e. countries that were most globalization-friendly at the start will tend to remain that way, even as the pandemic sweeps the world, while countries that were not highly globalized are unlikely to choose to become so during a pandemic.

Covid-19 Measures

There are a number of possible measures that could be used to estimate the intensity of the pandemic at different points in time. Some examples:

• Covid Infections per million population (cumulative or interval).

• Covid Cases per million population (cumulative or interval).

• Covid Deaths per million population (cumulative or interval).

• Covid Case Fatality Rate (cumulative or interval).

All of these have strengths and weaknesses. A major weakness is the reliability and accuracy of information collections between different countries and over time within countries. I will tend to focus on Covid Deaths per million population, as that seems likely have the best record-keeping (dead bodies are hard to ignore).

The Relationship between Globalization Intensity and the Covid-19 Pandemic

Below are a selection of graphs at various points in time (about six months apart), showing the Overall Globalization Index (the scale of which varies between about 30 and about 100) versus Deaths per Million population. The upper left hand corner of the graphs gives the R-square between these two measures, which can be thought of as the proportion of variance in the scatter-plot between these variables that can be explained by a linear relationship. In other words, how well do the points follow a straight line.

May 2020

• Early in the pandemic, most countries had rather low Deaths per Million Population, though a small number hit fairly high levels quite quickly.  Those tended to be the highly globalized countries, as measured by the Overall Globalization Index.
  

• The R-square was quite low (0.0457), indicating that not much of the variance was explained by the linear relationship (also visually obvious).

   

November 2020

• By autumn of 2020 the Deaths per Million Population had risen substantially in a lot of countries, though there were still many with very low death rates.

• The R-square (0.112) had risen a fair bit, so the linear relationship was now accounting for much more of the variance. Nonetheless, there is still a lot of scatter in the graph.

June 2021

• Deaths per Million Population had increased substantially (note the change in the scale of they y-axis from 0-1200, to 0-3000).

• The R-square was also substantially higher (0.280), so much more of the variance is now being explained by the linear relationship.

November 2021

• Deaths per Million Population continued to increase (note the change in the scale of they y-axis from 0-3000, to 0-6000).

• There is now one very high outlier, at nearly 6000 Deaths per Million.

• The R-square has dropped somewhat, to 0.206. This may be a seasonal effect, since at this point in time, one hemisphere will have experienced two winters, while the other has only experienced one winter. However, the differing mutational phases of the virus’s evolution may also have created this effect.

June 2022

• Deaths per Million Population have continued to increase.

• Several more countries have broken into the 4000 to 6000 Deaths per Million range.

• The R-square has gone back up (0.265), and is now nearly the same as it was in June 2020 (0.280). This would tend to support the idea that there is a seasonal effect that is responsible for the up-and-down in the R-square values.

Time Trend of Correlation and R-Square, Globalization Indices vs Deaths per Million Population

Having looked at some individual point-in-time graphs of Overall Globalization vs Covid-19 Deaths per Million, we can now put these together on one graph, along with some other points-in-time. In addition, we can look at the relationship between the other globalization measures (Social, Economic, Political) and the Deaths per Million Population Measure.

 

• Note that the lines for each of the globalization measures show similar trends.

• For the top graph, correlation coefficients have been used, rather than R-square measures. Technically, the correlation coefficient (R) is just the square root of R-square (thus the name), so this just results in a scale effect, but the overall tendency of the graphs are similar.  The next graph gives the R-Square relationship between Globalization Measures and Covid-19 Deaths per Million Population.
  

• The correlation (and R-Square) between globalization and deaths begins at a relatively low level, rises to a much highly level within a year (i.e. in four seasons), then drops a bit, and finally rises to about the same level at the end of two full years as it had been at the end of one year.

• Social Globalization had the highest correlation with Deaths, followed by Economic Globalization, then finally Political Globalization at quite a bit lower level. The Overall Globalization measure (a combination of the three other measures) is not too far off the Social Globalization measure.

• So, it seems that the movement of people (Social Globalization) had the most profound effect on the spread of the pandemic, followed the movement of things (Economic Globalization). Political Globalization was not so closely tied to the pandemic, perhaps because it is a more legalistic measure and thus had less of an organic relationship with the pandemic (viruses don’t travel on treaties).

   
  

There are some other interesting globalization aspects to the Covid-19 pandemic, which I will look at in a later blog.

Some earlier Covid-19 blogs:

https://dodecahedronbooks.blogspot.com/2021/07/covid-19-cases-and-deaths-by-continent.html

https://dodecahedronbooks.blogspot.com/2021/07/covid-19-cases-by-continent-jan-2000-to.html

https://dodecahedronbooks.blogspot.com/2021/03/covid-19-vaccines-how-successfully-are.html

https://dodecahedronbooks.blogspot.com/2020/12/covid-19-vaccines-comparison-of.html

https://dodecahedronbooks.blogspot.com/2020/09/covid-19-continues-to-travel-around.html

https://dodecahedronbooks.blogspot.com/2020/07/has-covid-19-become-less-deadly.html

https://dodecahedronbooks.blogspot.com/2020/07/july-2020-update-covid-19-death-rates.html

https://dodecahedronbooks.blogspot.com/2020/05/covid-19-death-rates-correlate-highly.html

https://dodecahedronbooks.blogspot.com/2020/06/covid-19-impact-on-employment-no-impact.html

https://dodecahedronbooks.blogspot.com/2020/04/is-there-model-that-can-predict-when-to.html

https://dodecahedronbooks.blogspot.com/2020/03/estimating-fatality-rate-of-coronavirus.html

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And, here’s a more pleasant travel story than anticipating the worldwide journey of a virus.

A Drive Across Newfoundland

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Newfoundland, Canada’s most easterly province, is a region that is both fascinating in its unique culture and amazing in its vistas of stark beauty. The weather is often wild, with coastal regions known for steep cliffs and crashing waves (though tranquil beaches exist too). The inland areas are primarily Precambrian shield, dominated by forests, rivers, rock formations, and abundant wildlife. The province also features some of the Earth’s most remarkable geology, notably The Tablelands, where the mantle rocks of the Earth’s interior have been exposed at the surface, permitting one to explore an almost alien landscape, an opportunity available on only a few scattered regions of the planet.

The city of St. John’s is one of Canada’s most unique urban areas, with a population that maintains many old traditions and cultural aspects of the British Isles. That’s true of the rest of the province, as well, where the people are friendly and inclined to chat amiably with visitors. Plus, they talk with amusing accents and party hard, so what’s not to like?

This account focusses on a two-week road trip in October 2007, from St. John’s in the southeast, to L’Anse aux Meadows in the far northwest, the only known Viking settlement in North America. It also features a day hike visit to The Tablelands, a remarkable and majestic geological feature. Even those who don’t normally consider themselves very interested in geology will find themselves awe-struck by these other-worldly landscapes.

On the Road with Bronco Billy

Spring is on us now, and that brings on thoughts of ROAD TRIP. Sure, it is still a bit early, but you can still start making plans for your next road trip with help of “On the Road with Bronco Billy”. Sit back and go on a ten day trucking trip in a big rig, through western North America, from Alberta to Texas, and back again. Explore the countryside, learn some trucking lingo, and observe the shifting cultural norms across this great continent. Then, come spring, try it out for yourself.

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