Until now we have lived, with certain ups and downs, in the longest period of well-being that old Europe has seen in recent centuries. But SARS-CoV-2, or another of the pandemics that are sure to come, may end it.
At least, there was another long period of prosperity that ended as a consequence of a pandemic: The great historian Edward E. Gibbon maintained that the best time in history to lead a full and happy life occurred in Classical Rome, starting in the year 96 of our era.
During the reign of the so-called 5 good emperors, Nerva, Trajan, Adriano, Antonino and Marco Aurelio, Roman citizens, including women, enjoyed a time of extraordinary prosperity, progress, rights and freedoms. It was a period where culture was a precious asset, which generated an extraordinary proliferation of schools of logic, ethics, philosophy and medicine. It was perhaps the longest period in European history with the fewest armed conflicts: the Pax Romana.
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That long period of prosperity began to decline in the year 165 with a pandemic outbreak, the Antonine Plague, which would continue to reappear in successive waves for the next 15 years, devastating the entire Roman Empire. It is estimated that at least a third of its inhabitants died. Rome never recovered.
Galen described that plague in detail: it was smallpox (variola major).
Plague Antonina is reminiscent, in many ways, of COVID-19. Smallpox was produced by the Variola virus, an Orthopoxvirus whose spread is similar to that of SARS-CoV-2: from person to person through saliva droplets dispersed in the air. The virus was kept alive for about 24 hours on the surfaces where it fell.
It was a more contagious disease than COVID-19 and much more deadly. Those infected also transmitted the virus shortly after becoming infected, while they were still asymptomatic. Like now, the Romans had never been in contact with this newly arrived virus. They had no antibodies to the new virus. There was no “herd immunity”.
Smallpox was probably the worst viral disease that affected humanity. And the only one that we managed to eradicate from the face of the Earth, during the last century, through mass vaccination (all of us who are old enough have the smallpox vaccine brand on one arm, near the shoulder).
Emperor Marcus Aurelius wiser than those of today?
Emperor Marcus Aurelius, a Stoic sage, as well as rulers and scholars of the time – including Galen and many of his colleagues – strove to find the causes of the devastating Antonine Plague, reaching the most interesting conclusions:
Just like now, the plague came from the East. It reached Mesopotamia, on the edge of the Roman Empire and from there it spread throughout the Mare Nostrum.
The prosperity -and security- of the Pax Romana led people to travel a lot:
– Young people went to study in the academies and schools of Classical Greece in search of a good education. And from there they often went on to Alexandria.
– They also traveled to “see the world”.
– Mesopotamia was a mythical place that was good to know.
– In addition, tens of thousands of soldiers were going to reinforce the distant borders of the empire. At the end of their military service they returned.
– Rome demanded goods manufactured in distant places. Their main barn was in North Africa.
The Mediterranean was the way for rapid communications. The Empire was united by a huge merchant fleet that in a few days could communicate any port with each other. The smallpox virus was able to spread rapidly throughout the Roman Empire.
In view of this, the wise Marco Aurelio decided to renounce certain imperial conquests: those that for their maintenance needed greater movements of people, troops and logistics.
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Knowing the causes is the best way to get the solutions right
Just as Marco Aurelio tried to do 1855 years ago, it is worth finding out what factors are responsible for the coronavirus that has infected nearly 3,500,000 people worldwide, causing some 300,000 deaths. And what, unfortunately, still remains to be added.
It is the way of knowing, in a rigorous way, what were the causes that led to the disaster. And, without a doubt, it is the best way to find the right solutions for a world after COVID-19.
Today, we have much more data than Marco Aurelio, the most powerful man of his time, could even imagine.
For example, the numbers of people infected and killed by COVID-19 are updated daily.
We also have a multitude of accurate statistics that many international institutions (for example, the World Health Organization, the World Bank … and even the CIA) make available to scholars.
Here are the most reliable data from the vast majority of countries in the world, among others:
– A series of demographic indicators for each country (such as its urban population, the census of over 65 years, life expectancy …),
– precise estimators of its economy (such as its unemployment rate, its inflation, public investment in education …),
– data on the health structure (such as number of hospital beds and ICUs per inhabitant, number of doctors …),
– figures on its environmental quality (such as CO2 emissions, nitrogen oxide emissions, air quality …)
– and exact values of the total number of visitors who arrived in the country, together with a series of indicators of the ease of traveling through the interior of the country.
In addition, we have a huge computational processing capacity: a current personal computer is thousands of times more powerful than the NASA computers that took man to the moon.
This massive processing of a huge amount of information, together with the high calculation capacity, allows us to relate millions of data to each other.
Regression analysis
But by far the most important thing is missing: after more than 2,500 years of mathematics development, today we have sophisticated tools, such as regression analysis, that allow us to know the relationship between some response variables and i with a series of predictor variables xi (in In its simplest form, this mathematical model is a linear model of the form …
*To try to make us all understand it: regression analysis is a statistical method that allows us to examine the relationship between two or more variables to identify which ones have the greatest impact on a topic of interest.
Thus, a regression allows to determine with confidence which are the most important factors, which can be ignored and how they influence each other.
These factors are called variables and can be dependent (it is the most important factor, the one that you are trying to understand or predict) and Independent (it is the factor that the researcher believes can impact on that dependent variable).
Once we’ve explained it, let’s move on:
Of course, a large number of regression studies have already been done, are being done and will still be done: several hundred have already gone by since the start of COVID-19.
Most of them have immediate application to the clinic (for example, those who find that the older they are, or the blood pressure, they are more likely to die from COVID-19).
Others allow us to know what factors influenced and how much they did and what factors had nothing to do with the number of people infected and killed by COVID-19.
When drawing conclusions guided by scientific rigor and not ideology, regression analysis is essential.
We can study in a precise way the relationship between the number of people infected with COVID-19 (or the number of deaths from this disease) and a series of variables such as the number of people traveling to a given country, the degree of contamination of the country, its economic and social structure, its health, etc., in the different countries.
Although we have the data for 184 countries, we must bear in mind that the weight of giant countries such as China, the USA or Germany is going to be much higher than the weight of small countries such as Luxembourg, Monaco or Andorra.
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What the analysis tells us about the weight of travel
The results obtained from this regression analysis are most revealing:
Among the many causes studied, one of the most important – by far – was the number of travelers who, for pleasure or work, arrived in each country (the English term is inbound tourism).
The linear regression study between inbound tourism that reaches different countries and the number of people infected with COVID-19, or the number of deaths from the disease, indicates that there is a statistically significant positive regression in both cases (p
This means that the number of travelers who arrived in a country very well predicts the number of people infected or killed by COVID-19 that country had. And the probability that this prediction happened by chance is less than one in a hundred thousand.
The regression analysis allows us to estimate how many deaths from COVID-19 can be explained based on the number of travelers who arrived in the country. And the results are overwhelming: 63% of all deaths from COVID-19 in a country are explained by the number of travelers who arrived in that country.
What the analysis tells us about the weight of pollution
The environmental indicators (CO2 emissions, nitrous oxide emissions, energy consumption per inhabitant, etc.) also show a statistically significant regression (with p values
For example, 33% of those infected with COVID-19 are explained based on energy consumption. This does not mean that there is a direct cause and effect relationship between contamination and COVID-19. It only means that a country’s CO2 emissions or energy consumption very well predicts the number of people infected or killed by COVID-19 in the country. The different variables are usually correlated and the countries with the most emissions also often have a greater flow of travelers.
What the analysis tells us about the weight of the economy
Surprisingly, economic indicators had a much lesser influence on the number of infected or dead.
No statistically significant regressions were found between the different economic indicators and the rates of infection or death by COVID-19. P
Very rich countries like the United States have many infected and dead, while other rich countries have very few. Poorer countries like Portugal have very few infected and dead, while other poor countries (like some South Americans) have many.
The wealth of a country does not predict, at all, how many infected or dead it will have.
Neither do most of the general and demographic indicators of a country (such as its area, its population, its urban population, the average age of the population, the census of over 65 years, the growth rate, infant mortality, hope life, obesity rate …) showed a significant correlation with the virus, except for the indicators of the ease of traveling quickly within the country.
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Make no mistake: prevention is treatment
Regarding health and medical parameters, it should be noted that the number of those infected by COVID-19 is the best predictor of the number of deaths from this disease (p
And also in this case the results are overwhelming: 76% of all deaths from COVID-19 in a country are explained based on the number of infected people in that country.
Thus prevention, and not treatment, proved to be the best way to combat the disease.
The countries that did the most tests to isolate the infected earlier, and the countries that previously put in place rigorous containment measures, were by far the least affected.
The explanation for this result is that the existence of the SARS-CoV-2 coronavirus was unknown six months ago. There is no vaccine. There are no effective antiviral drugs and in sufficient quantity. In the worst moments of the pandemic, the coronavirus pushed healthcare beyond the limit in the vast majority of countries.
Doctors had few tools to fight the virus and still did not know how best to treat the infected.
An important clarification
In any case, it is necessary to make an important clarification: statistics find trends with large data sets. With figures of more than 3,500,000 infected and 250,000 dead, 100,000 infected or 10,000 dead above or below it has little statistical significance. However, on a human level 10,000 dead are a terrifying catastrophe.
Thus, although the enormous effort of the health workers did not save as many lives as good prevention would have done, each life saved is a triumph that we must thank them for.
We must think rigorously about all this: the massive confinement of more than half of humanity, together with the economic catastrophe that it entails, logically has not been very popular.
But the most conservative models indicate that, without confinement, there would have been a minimum of 20 to 50 times more deaths, although most likely the death toll could have reached the staggering 5,000,000.
We all want to get back to normal as soon as possible, but doing it too soon would be suicidal.
Without a doubt, the COVID-19 has been a huge blow for tourism. Faced with the threat of ruin, the sector wants to open as soon as possible. Press. It is understandable. But in Spain there are more than 25,000 families who have lost a loved one, often without being able to say goodbye to him and without honoring, properly, his death.
And, in this context, each million visitors who came to Spain in February could have cost 3,700 deaths from COVID-19.
Can we pay such a price?
