Prague University of Economics and Business
Faculty of Finance and Accounting
Department of Banking and Insurance
DIPLOMA THESIS
2021 Bc. František Bursa
Prague University of Economics and Business
Faculty of Finance and Accounting
Department of Banking and Insurance Field of study: Finance
Is the outbreak of coronavirus a Black Swan?
Author of thesis: Bc. František Bursa
Thesis supervisor: prof. Ing. Jaroslav Daňhel, CSc.
Year of defense: 2021
Proclamation of honesty
I proclaim that I completed the diploma thesis “Is the outbreak of coronavirus a Black Swan?” on my own, that I duly marked all the literature and other sources, which I used, and that I included all these sources in an attached list.
In on
Bc. František Bursa
Acknowledgements
My gratitude belongs to thesis supervisor, prof. Ing. Jaroslav Daňhel, CSc., who promptly provided me with useful advice during the whole process of creating this paper. Also, I am thankful for the support and encouragement that I was fortunate to receive from my parents and godfather. Above all, thanks be to God, whom I owe my life and all the gifts I was equipped with that make me and this piece of work completely unique.
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Abstract
The main topic of this diploma thesis is whether or not the current coronavirus pandemic could be regarded as a Black Swan event. The adverse economic situation together with overloaded health care providers and considerable challenges for the society as a whole raise the question if the pandemic situation could have been anticipated and prepared for in a better way. An analysis of the attributes typical of a Black Swan event (extreme impact, rarity, and prospective unpredictability) is applied to the COVID-19 pandemic.
The goal is to categorize the current situation. As the results show, pandemic situations are not rare events and the current one was anticipated; nonetheless, the impact of its global outbreak might be considered extreme. Therefore, the following question arises:
Are we able to predict precisely enough to prepare for future events? This thesis provides the reader with insight into the concept of Black Swan events, into examination of extreme impact of the outbreak of coronavirus, into examination of its prospective unpredictability, and into examination of rarity of such events. Additionally, the findings of this study might lead to a reconsideration of our reliability on forecasts and of our ability to prepare for the future.
Key words
COVID-19 pandemic, Black Swan event, forecasts
Abstrakt
Hlavním tématem této diplomové práce je, zda lze současnou pandemii koronaviru považovat za událost „černá labuť‟ či nikoli. Nepříznivá ekonomická situace spolu s přetíženými poskytovateli zdravotní péče a značnými výzvami pro společnost jako celek vyvolávají otázku, zda šlo pandemickou situaci předvídat a připravit se na ni lépe. Na pandemii COVID-19 je použita analýza atributů typických pro událost „černá labuť‟
(extrémní dopad, vzácnost a prospektivní nepředvídatelnost). Cílem je kategorizovat současnou situaci. Jak ukazují výsledky, pandemické situace nejsou vzácnými událostmi a současná pandemie se očekávala; dopad jejího globálního vypuknutí lze nicméně považovat za extrémní. Proto vyvstává následující otázka: Jsme schopni předpovídat dostatečně přesně, abychom se připravili na budoucí události? Tato práce poskytuje
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čtenáři vhled do konceptu „černých labutí‟, zkoumání extrémního dopadu vypuknutí koronaviru, zkoumání jeho prospektivní nepředvídatelnosti a zkoumání vzácnosti těchto událostí. Zjištění této studie mohou navíc vést k přehodnocení našeho spoléhání se na předpovědi a naší schopnosti připravit se na budoucnost.
Klíčová slova
pandemie COVID-19, černá labuť, předpovědi
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Contents
Introduction ... 8
1. A Black Swan according to Nassim Nicholas Taleb ... 11
1.1. Black Swan events ... 11
1.1.1. Epidemics as Black Swan events ... 12
1.2. The concept of Black Swan events ... 12
1.2.1. Randomness in relation to Black Swan events ... 12
1.2.2. Two different dynamics ... 13
1.2.3. Risk management ... 14
1.2.4. How to prepare for Black Swans? ... 16
1.3. Final remarks on Black Swan events ... 18
2. The extreme impact of coronavirus ... 19
2.1. Tail risk ... 19
2.2. Economic impact ... 20
2.2.1. Forecasted economic impact ... 21
2.2.2. Historical economic impact ... 26
2.3. Social impact ... 30
2.3.1. The root of the pandemic situation ... 31
2.3.2. Mental health during and after the pandemic ... 33
2.3.3. Other fields under the impact of the pandemic ... 36
2.4. Final remarks on the impact of the COVID-19 pandemic ... 37
3. Comments on rarity and prospective unpredictability of the virus ... 40
3.1. Rarity ... 40
3.1.1. Rarity of pandemic situations ... 40
3.1.2. Are crises (such as the current pandemic crisis) rare? ... 41
3.1.3. Rarity of the virus ... 41
3.2. Prospective unpredictability of the virus ... 42
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3.2.1. An approach based on reference ... 43
3.2.2. A historical approach using bond yields: the theoretical part ... 46
3.2.3. A historical approach using bond yields: the practical part ... 47
3.3. Final remarks on rarity and prospective unpredictability of the virus ... 49
Conclusion ... 51
A short summary of the work ... 51
The results of the work ... 53
Sources ... 55
List of figures ... 60
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Introduction
The main topic of this paper is research on the outbreak of coronavirus disease (the COVID-19 pandemic) in terms of its attributes; particularly, the three main attributes of Black Swan events will be examined: extreme impact, rarity, and prospective unpredictability. As a result, the current pandemic situation will be categorized as a Black Swan event or a common event (a “white swan” event). The three mentioned attributes will be regarded as qualitative variables; therefore, the following questions will be asked:
“Does this pandemic have an extreme impact?”
“Are pandemics rare events?”
“Was the pandemic prospectively unpredictable?”
If all the answers are affirmative, the current pandemic will be classified as a Black Swan event.
What is not the topic of this paper? The mentioned three attributes will not be examined through quantitative viewpoint. Hence it will not be studied (in terms of precise measurements), how extreme the impact is; how rare pandemics are; how predictable the pandemic was: it will just be tested, whether or not the current pandemic is extreme enough in its impact, rare enough in its occurrence, and unpredictable enough in the period before its outbreak to be classified as a Black Swan event. Additionally, the extremity of impact will be monitored mainly for the USA, not globally.
To turn to the reason for studying the described topic, I consider the current pandemic crisis to be a serious issue for the economy and health care systems. I ask myself if we could have prepared (in a better way) for this event (in case it is not a Black Swan event).
Consequently, the main goal of this paper is to test whether or not the current pandemic is a Black Swan event. I hope this work will enrich contemporary literature on the COVID-19 pandemic and raise awareness of Black Swan events and of our inability to predict (precisely). The secondary goal is to try to find out whether it is possible at all to
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prepare for future events (that are predictable or unpredictable) or it is not in our nature to do so, taking into account the impact of this pandemic situation.
With reference to literature regarding the topic of Black Swan events, the main source will be the book The Black Swan: Second Edition: The Impact of the Highly Improbable:
With a new section: "On Robustness and Fragility" by Nassim Nicholas Taleb, who is the author of the concept of Black Swan events. Researching literature, I found two articles (McGillivray 2020; Avishai 2020) that deal with the question of whether or not the coronavirus pandemic is a Black Swan event; however, they are very brief. Therefore, I decided to put the outbreak of coronavirus to the test myself. When it comes to literature regarding the particular attributes of Black Swans, the impact of the COVID-19 is quite a popular topic. In contrast, rarity and prospective unpredictability of the event are not largely featured in literature.
As for methods of this scientific work, mainly logical methods are represented. At first, an analysis of the concept of a Black Swan event is conducted with the main focus on the three attributes: extreme impact, rarity, and prospective unpredictability. Then experimental methods are employed in order to test the particular conditions:
observations of extreme impact, rarity, and prospective unpredictability in the past serve as tools for experimentation. In the end, a synthesis of the findings takes place in order to reach a conclusion about the nature of the outbreak of coronavirus in relation to the concept of Black Swan events.
That brings me on to the structure of this paper. The main content of the paper begins with the description of the concept of Black Swan events. This description focuses on the representative Black Swans events, main attributes of such events, and a recommended preparation process for such events. Next the paper continues with experimental part dealing with different viewpoints on the particular conditions. First, the extreme impact of coronavirus is tested from the point of view of the economy, society, and individual.
Second, rarity is tested from the point of view of past pandemics, past crises, and past related viruses. Third, prospective unpredictability is tested from the point of view of
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references to the potential pandemic before the outbreak, and historical approach based on yield movements of a certain type of government bonds (the U.S. 10-year Treasury notes).
Now attention will be shifted to the concept of Black Swan events in the upcoming chapter.
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1. A Black Swan according to Nassim Nicholas Taleb
1.1. Black Swan events
In this chapter, theoretical background concerning Black Swan events will be provided.
The author of the term “Black Swan” is Nassim Nicholas Taleb. According to Taleb (Taleb 2010, s. 17), a Black Swan has three main attributes: rarity, extreme impact, and retrospective predictability.
First, it is significant to Black Swans that they are rare in their occurrence. The success of the book series Harry Potter by J. K. Rowling is an example of a Black Swan. Seldom are more than 100 million copies of a single book sold (120 million copies of Harry Potter and the Philosopher’s Stone were sold (Wikipedia 2020h)), not to mention the magnitude of sales of the whole series. Yet, events like these happen; it is just highly unlikely given the statistical data on book sales that we have.
Second, caring extreme impact is another typical trait of a Black Swan. For instance, the September 11 attacks had an extreme impact in terms of deaths, which illustrates a Black Swan with a negative impact. However, a discovery of penicillin by Alexander Fleming helped to save many lives, which illustrates a Black Swan with a positive impact.
Third, Black Swan events are retrospectively predictable, which means that we are able to provide explanation for their occurrence only after they happen. In other words, as the common Czech saying goes: after a battle everyone is a general. However, as highlighted by Taleb (Taleb 2010, s. 17), these events are not prospectively predictable given the knowledge that we possess right now.1 One example of such an event is the stock market crash on 19 October 1987 (commonly referred to as Black Monday (Wikipedia 2020b)).
Interestingly, being a Black Swan to some people, the same event is prospectively
1 Conversely, Taleb mentions that if an event that is expected to almost certainly happen does not happen, it is also a Black Swan event. (Taleb 2010, s. 17)
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predictable to others. To illustrate, the September 11 attacks were not Black Swans for the terrorists who planned the criminal deed. (Taleb 2010, s. 18)
To summarize, events might be considered Black Swans only after taking into account all the mentioned criteria: rarity, extreme impact, and prospective unpredictability.
1.1.1. Epidemics as Black Swan events
As Taleb puts it, “Fads, epidemics, fashion, ideas, the emergence of art genres and schools. All follow these Black Swan dynamics.” (Taleb 2010, s. 18) That is why I decided to apply the above mentioned 3 criteria to test whether or not the outbreak of coronavirus is a Black Swan event.
1.2. The concept of Black Swan events
1.2.1. Randomness in relation to Black Swan events
2In order to be able to determine whether or not we could be dealing with a Black Swan (and if yes, how we might measure it), it is important to differentiate between two realms of randomness: mild and wild.
First, mild randomness is typical for variables such as height or weight. The typical bell curve, invented by Carl Friedrich Gauss, is suitable for use here3, as even an extreme observation does not have a heavy impact on the whole. For instance, imagine a very heavy person’s weight in comparison with the weight of a certain large sample of people.
(Mandelbrot a Taleb 2006, s. 1)
Second, wild randomness is typical for variables such as wealth, deaths in wars, changes in exchange rates or interest rates. Contrary to mild randomness, the bell curve should not be used. Mandelbrot and Taleb recommend using a fractal scale in these situations. A
2 This section’s main information source is the article by Mandelbrot and Taleb: “A focus on the exceptions that prove the rule.” (Mandelbrot a Taleb 2006)
3 Regarding qualitative variables, Taleb says: “If you’re dealing with qualitative inference, such as in psychology or medicine, looking for yes/no answers to which magnitudes don’t apply, then you can assume you’re in Mediocristan without serious problems.” (Taleb 2010, s. 253) According to Taleb, being in Mediocristan means: using the bell curve is appropriate (as can be seen in Picture 1 that follows).
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single observation in the realm of wild randomness can have a dominant impact on the data set. To illustrate, consider the richest person’s wealth in relation to the wealth of a sample of population (a sample equally large in quantity of observations as the sample in the previous paragraph). Wild randomness might be visualized using distributions with fat tails, which will be described in the next chapter. (Mandelbrot a Taleb 2006, s. 1–2)
By and large, Black Swan events occur in realms of wild randomness. This is where we might expect such events. Number of deaths in an epidemic belongs to this realm, as will be shown in the following chapter.
1.2.2. Two different dynamics
To continue with the division between mild and wild randomness, Taleb uses mild and wild randomness also in defining “two dynamics”: Mediocristan and Extremistan, which he refers to throughout his book The Black Swan: Second Edition: The Impact of the Highly Improbable: With a new section: "On Robustness and Fragility". (Taleb 2010, s. 60) These two dynamics, summarized in Picture 1, help to better understand the concept of Black Swan events.
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Picture 1
Source: (Taleb 2010, s. 61)
According to Taleb, the problem arises when we act as though Black Swans did not exist.
It stems from “our blindness to the Black Swan”, our belief that we live in “Mediocristan.”
(Taleb 2010, s. 73) However, as defined in Picture 1, Taleb considers our modern environment to be more similar to “Extremistan,” which is subject to extreme Black Swan events.
1.2.3. Risk management
To illustrate, Taleb provides an example of the ludic fallacy, referring to the illusion that models based on a probability distribution in a game are applicable to the real world. He
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narrates a story about a certain casino in Las Vegas and the two types of risk (of potential losses) that it faced and is facing on a daily basis.4
On the one hand, the casino has to deal with a potentially very lucky player who could be lucky enough to win a tremendous amount of money. However, due to diversification of operations/games, the casino is relatively safe from this danger. Taleb notes, that this is one of the few instances when the bell curve is applicable for calculating probability.
(Taleb 2010, s. 147) It stems from the stable conditions/set of rules in the games played in casino, which do not change. The only other way somebody could beat the system used in casinos is by cheating, which is highly monitored.
On the other hand, the casino had to deal with other losses that were unexpected and not taken into account (not related to the games at all). These losses nearly destroyed the company financially. Particularly, Taleb mentions the following 4 events that cost the casino dangerously large amounts of money. First, the main performer in a show in the casino was bitten by his tiger and the casino was not able to substitute him. Therefore, the company lost around 100 million dollars. Second, a construction worker got injured at the construction of an adjacent hotel (belonging to the casino) and wanted to take his revenge by trying to blow the casino up with dynamites. Fortunately, the security stopped him. Third, due to an employee‘s mistake of neglecting to send certain documents about players to the tax authority, the casino had to pay a heavy fine. Fourth, the daughter of the casino‘s owner was kidnapped and the owner of the casino broke the law by taking money from the cash box. Fortunately for the casino, none of these real-world risks were extreme enough to force it to go bankrupt.
In conclusion, as is visible from the example of the casino, the current environment is prone to Black Swan events, and models/techniques that do not take this into consideration may not be applicable as effective tools for risk management. (Taleb 2010, s. 150)
4 The author of the story and ideas related to the example of casino is Taleb. (Taleb 2010, s. 148–150)
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1.2.4. How to prepare for Black Swans?
Is it even possible to get ready for rare, unpredictable events that carry extreme impact?
Taleb asserts that it is possible by searching for opportunities whose positive consequences outweigh negative ones. (Taleb 2010, s. 222) He gives the following 5 recommendations.
“First, make a distinction between positive contingencies and negative ones.” (Taleb 2010, s. 219) Taleb names certain fields that are usually affected by negative Black Swans: military, catastrophe insurance, homeland security, banking and lending. (Taleb 2010, s. 219) He also points to the fields that are more likely to be hit by positive Black Swans: movies, some segments of publishing, scientific research, and venture capital.
(Taleb 2010, s. 219)
“Don’t look for the precise and the local.” (Taleb 2010, s. 220) Taleb proposes focusing on preparedness rather than on producing exact forecasts. He recommends working hard to be ready for unexpected events of various types, not just few particular Black Swans.
(Taleb 2010, s. 220–221)
“Seize any opportunity, or anything that looks like opportunity.” (Taleb 2010, s. 221) He justifies this advice by explaining how rare opportunities are. Therefore, it is necessary to utilize these chances, to expose ourselves intentionally to positive Black Swans. (Taleb 2010, s. 221)
“Beware of precise plans by governments.” (Taleb 2010, s. 221) This comment highlights the necessity to be cautious when faced with prognoses of various types (not just from government, but also from banks, or corporations). According to Taleb, prognoses and forecasts are, unfortunately, often produced by their authors just to “survive”, not in order to look for the truth, which might be misleading. “Getting their yearly bonus” might be a stronger motivation for managers in corporations, producing seemingly (short-term) good results. (Taleb 2010, s. 221–222)
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“Do not waste your time trying to fight forecasters, stock analysts, economists, and social scientists, except to play pranks on them.” (Taleb 2010, s. 222) Again, Taleb warns about predictions and supports his claim by the fact that some people are paid to make predictions; therefore, they are likely to be stubborn about their point of view. (Taleb 2010, s. 222)
He calls these recommendations “tricks” of how to cope with Black Swans. Taleb also mentions a “barbel strategy” that he used as a trader, which illustrates his defense mechanisms in the area of investing. He would invest 85-90 % of money in relatively very safe assets, such as Treasury bills. The rest would be allocated to “extremely speculative bets, as leveraged as possible (like options), preferably venture capital–style portfolios.” (Taleb 2010, s. 218) Taleb also mentions the possibility to use a certain type of insurance as an effective tool against negative Black Swan events: “Or, equivalently, you can have a speculative portfolio and insure it (if possible) against losses of more than, say, 15 percent. You are “clipping” your incomputable risk, the one that is harmful to you.” (Taleb 2010, s. 218)
To conclude, the following statement by Taleb encapsulates his approach to preparation for Black Swan events: “I worry less about embarrassment than about missing an opportunity. In the end this is a trivial decision making rule: I am very aggressive when I can gain exposure to positive Black Swans—when a failure would be of small moment—
and very conservative when I am under threat from a negative Black Swan.” (Taleb 2010, s. 299–300)
By reading Taleb‘s book The Black Swan: Second Edition: The Impact of the Highly Improbable: With a new section: "On Robustness and Fragility", I noticed one personality trait that sums up the idea of being prepared for a potential Black Swan: open- mindedness. In other words, respect opinions and ideas of other people as they probably are potentially valuable sources of information for you or somebody else.
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1.3. Final remarks on Black Swan events
The attributes of the “real” world, in which we live, enable the existence of Black Swans.
These events might be wild and extreme in their impact; therefore, it is credible to accept the existence and possibility of occurrence of such events. As claimed by Taleb, there are potentially viable approaches of how to prepare for them, even if we cannot predict them.
Rarity, extreme impact, and prospective unpredictability are typical of Black Swan events. These three conditions will be tested (in the next two chapters) in relation to the outbreak of coronavirus in order to find out whether or not this event might be considered a Black Swan event.
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2. The extreme impact of coronavirus
To assess the extreme impact of coronavirus, there are a number of viewpoints to be taken into account. For instance, we can look at it from the perspective of tail risk. In other words, how probable is it that the consequences of this pandemic will be extreme? Or we might observe the economic (such as an increase in mortality, a decrease in GDP, and an increase in unemployment rate), social implications (psychological burden connected to social distancing and loneliness; fear of infection or death; high levels of anxiety), and, perhaps, other implications (faced by individuals in their surroundings) that are carried by the pandemic situation.
2.1. Tail risk
In the article “Tail risk of contagious diseases” in Nature Physics, Cirillo and Taleb manifest that the distribution of fatalities connected to pandemics is a fat-tailed distribution. (Cirillo a Taleb 2020, s. 606) In regard to the article, basic properties of a fat-tailed distribution, and events comparable to a pandemic will be examined more closely.
Firstly, what is a typical property of a fat-tailed distribution? According to Cirillo and Taleb, “. . . the more fat-tailed a statistical distribution, the more the ‘tail wags the dog’.
That is to say, more statistical information resides in the extremes and less in the ‘bulk’ . . .” (Cirillo a Taleb 2020, s. 606–607) Having a fat-tailed distribution, the current pandemic might have an extreme impact in terms of fatalities.
Secondly, Cirrilo and Taleb highlight the potentially extreme impact of coronavirus by noting that “. . . only war casualties and operational risk losses show a behaviour as erratic and wild as the one we observe for pandemic fatalities.” (Cirillo a Taleb 2020, s. 606)
In conclusion, the facts that the COVID-19 pandemic has a fat-tailed distribution, and that it is comparable to events such as wars in terms of potential fatalities provide a proof that the coronavirus pandemic has a potentially extreme impact. Accordingly, it may be implied the coronavirus pandemic has a property that is typical of Black Swan events.
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2.2. Economic impact
There is a lot of ways in which pandemics affect the economy on the local and global level. These effects will be examined with the assistance of forecasts and historical data.
Numerous reasons stand behind stressing the situation in the USA and providing examples of economic development in this country.
To begin, the USA has immense influence on the global economy. As documented by Dees and Saint-Guilhem, “The U.S. economy is often seen as ‘the engine’ of the world economy. As a result, any sign of slowdown in the United States raises concerns about harmful spillovers to the other economies.” (Dees a Saint-Guilhem 2011)
Next, Roubini and Mihm comment on global impact of the economy of the USA: “An old saying in financial markets has it that ‘when the United States sneezes, the rest of the world catches a cold.‘ However clichéd, that observation contains plenty of truth: the United States is the biggest, most powerful economy in the world, and when it gets sick, countries that depend on its insatiable demand for everything from raw commodities to finished consumer goods find themselves in trouble too.” (Roubini a Mihm 2010, s. 60) Therefore, there could be reason to be alerted by the currently quickly rising numbers among infected and dead people in the USA (as will be documented in the next paragraph, the USA tops the table): inflicted economic issues on this country might spill over into the global economy in a very powerful way.
Moreover, the number of total deaths in the USA is the highest among all countries, with more than 160 thousand as of 13.8.2020. (Worldometer 2020; WHO 2020b) Since the goal of this chapter is to test the extremity of impact of the current pandemic (and taking into account the mentioned global effect of changes in the economy of the USA), this country seems like a plausible candidate for analysis.
On top of that, the essential data is conveniently available in the case of the United States.
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2.2.1. Forecasted economic impact
To illustrate possible channels of impact, we can look at Lee and McKibbin’s approach in relation to the SARS outbreak (2002-2004).5 Although SARS outbreak was defined as an epidemic (affecting more than 8000 people with infection and causing approximately 774 deaths), it is similar to the current pandemic in its international spread. (Wikipedia 2020a) Lee and McKibbin enumerate the channels of impact in the form of medical expenditures; demographic consequences (due to forgone incomes); decline in consumer demand (mostly in travel and retail sales services); loss of foreign investors’ confidence;
and costs of disease prevention, with the last three being the most significant for SARS.
(Lee a McKibbin 2004, s. 116–117) Presumably, all these channels are significant for the COVID-19 pandemic, with 680 894 confirmed deaths as of 2 August 2020. (WHO 2020a)
The results of the study by Lee and McKibbin show that the real economic impact could be very large, especially for the countries with the most cases of SARS-CoV-1, which were China and Hong Kong. They also note that the real economic costs exceed the medical costs by far. The authors conclude the article with the following assumption: “If the threat of recurring SARS or SARS-like diseases from China is real, then the estimated risk to economic activity in the region and the world, as calculated in this paper, could be very large.” (Lee a McKibbin 2004, s. 130) For that matter, SARS-CoV-2, once again originating in China, could fulfill this anticipation.
Next, McKibbin and Fernando, using the modeling technique from the study mentioned in the preceding paragraph (called the G-Cubed model: simple overview of the model will be pictured in Table 1), model the possible economic outcomes of SARS-CoV-2 infection, providing 7 scenarios. (McKibbin a Fernando 2020) The first three scenarios are cases of infection being confided to China (epidemic situation in China); scenarios 4- 6 expect a pandemic situation; the seventh scenario counts with a mild annually recurring pandemic situation (the first 6 scenarios are modelled as temporary). The resulting modelled mortality and GDP loss in 2020 for specific countries/regions are visualized in
5 Severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) was responsible for the 2002-2004 SARS outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is causing the current coronavirus disease pandemic (COVID-19 pandemic). (Wikipedia 2020j)
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Tables 2, 3, and 4. All the results constitute the difference between a particular scenario and the situation of no coronavirus outbreak (baseline situation).
Table 1 - Overview of the G-Cubed (G20) model
Source: McKibbin a Fernando (2020)
Table 1 pictures the countries and regions (24 altogether) in the model, which also the following tables (Table 2, 3, and 4) comprise.
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Table 2 - Impact on populations under each scenario
Source: McKibbin a Fernando (2020)
As can be seen in Table 2, the authors came to the conclusion that only a slight pandemic situation could result in more than 15 million deaths worldwide. Currently, the death toll of coronavirus pandemic is 690 257 as of 4 August 2020. (WHO 2020a) However, as outlined in the section Tail risk, the current pandemic with a fat-tail distribution should not be underestimated. In spite of this, is the impact extreme? As Cirillo and Taleb show in their article “Tail risk of contagious diseases”, if we took into account the current world’s population, the pandemic called “Plague of Justinian” or the one called “Black Death” would kill more than 2 billion of the world’s population (each). (Cirillo a Taleb 2020, s. 608–609)
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Table 3 - GDP loss in 2020 (% deviation from baseline)
Source: McKibbin a Fernando (2020)
To continue, it is obvious from Table 3 and Table 4 that even the slightest pandemic scenario (S04) would have severely adverse consequences globally for the economic growth in terms of GDP. For instance, the forecast suggests that in S04 the GDP loss of the USA in 2020 would be -2 %, accounting for the loss of 420 billion $US. In comparison, the GDP loss of the USA in 2009 (connected to the bankruptcy of Lehman Brothers in September 2008 and the global financial crisis) was approximately -2,537 %, according to the database of the World Bank. (The World Bank 2020) What is more, the International Monetary Fund (IMF) issued the “World Economic Outlook Update” for
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2020 where the IMF projects the GDP loss of the USA in 2020 to be -8 %, choosing a title “A Crisis Like No Other, An Uncertain Recovery” for the description of the current situation. (IMF 2020, s. 1) That makes the current situation look more like the worst pandemic situation in Table 3 (S06: based on the attributes of the Spanish flu) and points to the fact that economic impact of this crisis might be unprecedented.
Table 4 - GDP Loss in 2020 ($US billions)
Source: McKibbin a Fernando (2020)
All in all, the model by McKibbin and Fernando and other above-mentioned sources indicate that the economic impact of the coronavirus pandemic might be extreme.
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2.2.2. Historical economic impact
To continue with the example of the USA, a quarterly GDP development following an event of immense significance in relation to the global financial crisis (the bankruptcy of the Lehman Brothers in September 2008) and in relation to COVID-19 (the announcement of a pandemic situation in March 2020) will be confronted. According to the database of the Organisation for Economic Co-operation and Development (OECD), the quarterly GDP change (measured as percentage change from the previous period) for the USA for the second quarter of 2020 was -9,5 %; the quarterly GDP change (measured as percentage change from the previous period) for the USA for the fourth quarter of 2008 was -2,2 %. (OECD 2020a) To highlight the severity of difference between those two numbers, the global financial crisis originated in the USA, whereas the coronavirus broke out in Wuhan, Hubei, China. Moreover, the subsequent quarterly data on GDP change in the USA (for the first quarter of 2009) imply an improvement, to be precise the quarterly GDP change for this period is -1,1 %. (OECD 2020a) Whether there will be a continuation in the present downward trend of GDP change or not is yet to be seen. On the whole, the historical impact of the coronavirus pandemic looks much more extreme than the impact of the global financial crisis so far, considering the GDP growth.
Similarly, the historical data on employment underline the intensity of the crisis induced by COVID-19. The OECD in their book OECD Employment Outlook 2020: Worker Security and the COVID-19 Crisis brings to attention that the changes in employment are due to a decline in the number of employed people and a decline in the number of hours worked. The authors go on to remark: “…on average across the countries for which data are available, total hours worked fell by 12.2% in the initial three months of the crisis compared to 1.2% of the first three months of the global financial crisis.” This message is visualized in Picture 2, taken from the mentioned book. (OECD 2020b, s. 37)
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Picture 2
Source: (OECD 2020b)
As for Picture 2, it is visible that (for the countries with available data: Australia, Canada, Japan, Korea, Sweden, the United Kingdom, and the United States) percentage change in total hours worked with respect to hours worked in the month of the onset of the crisis (October 2008 for the global financial crisis for all countries; January 2020 for Japan and February 2020 for all other countries for the COVID-19 crisis) was markedly higher in the case of the COVID-19 crisis. Therefore, it may be implied that the negative economic impact of the current crisis has had greater dimensions (in terms of change in total hours worked).
When it comes to unemployment rate in the USA, the latest available data also speak in favor of the high severity of the COVID-19 pandemic. According to the U.S. Bureau of Labor Statistics (BLS), the unemployment rate for April 2020 was 14,7 %: a maximum for the period from January 1948 until now. The data for this period are seasonally
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adjusted and take into account the unemployment rate for the age group of 16 years and older. (BLS 2020) Compared to periods of other historical severe recessions, the unemployment rate peaked in October 2009 (probably connected to the global financial crisis) at 10,0 %; the unemployment rate peaked also in November and December 1982 (probably connected to the early 1980s recession) at 10,8 %. Therefore, the labor market seems to have been hit most severely by the current pandemic for the whole period from 1948. However, if we look at the data from BLS before 1948, which are not seasonally adjusted (yearly data) and refer to the age group of 14 years and older, the unemployment rate peaks in 1933 at 24,9 % (probably connected to the Great Depression, as the unemployment rate was just 3,2 % in 1929). (Roubini a Mihm 2010, s. 14; BLS 2020)
Picture 3
Source: (Irum a Hudgins 2020)
Now for bankruptcies, Picture 3 shows data on bankruptcies of larger (as defined at the bottom of the picture) public and private companies in the USA compiled by Standard and Poor’s Global Market Intelligence. (Irum a Hudgins 2020) The chart displays that the number of large companies’ bankruptcy filings in the USA is already (as of 10 August
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2020) quite high compared to the previous 10 years (bearing in mind year-to-date numbers), with only the figure from 2010 being higher.
Picture 4
Source: (Irum a Hudgins 2020)
As can be seen in Picture 4, large companies operating in the sector Consumer discretionary6 have been most severely hit by the current pandemic, followed by the sectors Industrials; Energy; and Healthcare. On the other hand, sectors Financials, and Utilities have been the least affected.
Even though the number of bankruptcy filings by larger firms in the USA (as shown in Picture 3) is quite alarming, the number of all business bankruptcy filings in the USA has not indicated any significant change from last year (as can be seen in Figure A.1 and A.2 in List of figures at the end of this paper). At the level between 5 and 6 thousand filings
6 This sector might be defined as “. . . goods and services that are considered non-essential by consumers, but desirable if their available income is sufficient to purchase them. Examples of consumer discretionary products can include durable goods, high-end apparel, entertainment, leisure activities, and automobiles.”
(Investopedia 2020)
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quarterly, the business filings in the first two quarters of 2020 have not deviated much from the quarterly levels in the previous year or in the year 2018. By contrast, the number of business bankruptcy fillings reached 16 thousand in the second quarter of 2009 (succeeding the financial crisis of 2007-2008) and 26 thousand in the second quarter of 1987.
As far as quarterly non-business filings in the USA are concerned, the situation is calm with a descending trend, reaching a minimum (in the second quarter of 2020) since the first quarter of 2006 (see Figures B.1-B.6 in List of figures at the end of the document).
However, the percentage of Chapter 7 filings7 in the second quarter of 2020 reached a maximum since the fourth quarter of 2005.
In conclusion, historical economic impact of the coronavirus pandemic seems to have been quite extreme in the last months. Together with the extreme forecasts, this impact might emerge to be extreme enough to meet one of the conditions of a Black Swan event.
2.3. Social impact
The pandemic situation has caused some profound social issues. Education slowed down or ceased (as a result of school closures); religious, cultural, and sport events became limited; social life as a whole diminished. The threat of a serious disease together with a voluntary social isolation or the necessity to stay in quarantine (either due to having been diagnosed with COVID-19, or due to having been in contact with such a person) might have an adverse effect on mental health of population, not to mention the physical health risk posed by the coronavirus itself. Additionally, there is still the mystery revolving around the origin of the coronavirus disease (whether or not it stems from a bioterrorist attack).
7 Chapter 7 bankruptcy filing results in liquidation of assets. Chapter 13 bankruptcy filing is for individuals with an income above certain threshold, and results in a debt repayment plan. (Tuovila 2020) Therefore, this rise in the stated percentage might demonstrate a downward shift in incomes.
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Hyams et al. remark that CBN (chemical, biological, or nuclear) weapons belong to a group of “health hazards that are likely to cause both public fear and heightened anxiety.”
(Hyams et al. 2002, s. 274)
The authors add: “A large body of research has indicated that the following features of a health threat are associated with prolonged effects:
(1) involuntary threats that occur without warning (as opposed to personal choices like cigarette smoking),
(2) manufactured threats versus natural disasters (‘acts of God‘), (3) unfamiliar threats with unknown health effects, and
(4) threats that pose a danger to children and future generations.”
(Hyams et al. 2002, s. 274)
The current pandemic shows most of these features and therefore may be regarded as a health threat that has prolonged effects, e.g. on mental health (in terms of fear and anxiety) and social behavior (such as distancing/isolating from others or wearing a mask due to a risk of contagion)8. Probably the only variable is whether the threat (in form of a deadly virus) was manufactured (as an act of bioterrorism), or the outbreak of virus occurred naturally.
2.3.1. The root of the pandemic situation
As for the origin of SARS-CoV-2, Mark Kortepeter, an infectious disease and public health physician, provides insight into the process of determination whether or not the COVID-19 stems from deliberate bioterrorism in his article “Did Covid-19 Come From A Lab? Was It Deliberate Bioterrorism? A Biodefense Expert Explores The Clues.” The author defines “some ‘red flags’ of a suspicious outbreak” (Kortepeter 2020):
1) Previously effective treatments don’t work.
2) The outbreak occurs in an unusual location.
3) There’s no vector for disease transmission.
4) The disease spreads in a “downwind plume” pattern.
8 Even if there is a vaccine at the end of 2020, social distancing and wearing masks will probably still be recommended in order to limit the spread of the virus. The reason for this is that the vaccine is reckoned highly unlikely to be 100 % effective. The effectivity is presumed to lie between 70 and 75 percent. (Fottrell 2020) Therefore, prolonged effects might be expected.
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5) The disease presents with unusual symptoms.
6) There’s no previous presence of the disease in animals.
7) There’s evidence of deliberate genetic manipulation.
With reference to the listed points, the author of the mentioned article argues that only some of these points indicate “a suspicious outbreak.” Regarding the first point, there has never been an effective treatment for any of the coronaviruses. Additionally, SARS-CoV- 2 is a brand new type of coronavirus. The second point is not “a red flag” either, since SARS-CoV-1 originated in China too, and coronaviruses have been found in bats in this country. As for the third point, no vector (such as a mosquito) is needed, since COVID- 19 is spread through airborne droplets. When it comes to the fourth point, a “downwind plume” pattern is not significant for this type of virus: it is transmitted from person to person through airborne droplets. To continue with the point 5, the COVID-19 has presented so far mostly with usual symptoms (usual for diseases caused by coronaviruses). The point six is “a red flag” because SARS-CoV-2 has not been found in any animal yet (except for other coronaviruses in bats), which points out to no previous spillover event and therefore a possible human intervention.9 The seventh point also rises
“a red flag”. To put it another way, there is still quarrel in scientific community about whether this particular type of virus is man-made or evolved naturally. (Kortepeter 2020)
In order to resolve this issue of the origin of the virus, a thorough investigation, involving identifying the exact type of virus in the first infected humans and comparing it to the virus in Wuhan laboratory (where it allegedly originated) and the corresponding type of virus in animals, must take place. However, as the author notes, even in the case of identical versions of virus (genetically) in Wuhan laboratory and the first victims of the COVID-19, there is still a question about whether the virus got out from the laboratory coincidentally or somebody intentionally started the spread of it (as an act of bioterrorism). (Kortepeter 2020)
9 According to the author of the article, Mark Kortepeter, spillover event is a transmission of infection from animals to humans. It is typical for zoonoses: pathogens that are present in animals. (Kortepeter 2020)
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With reference to the intentional spread of SARS-CoV-2, we need to look at the possible reasons why somebody would cause (or be otherwise involved in) the pandemic situation.
Undoubtedly, there are companies and individuals that might profit from the current situation: such as companies producing goods that protect people from the virus (masks, disinfectants, and other medical goods necessary for handling the current situation by both medical professionals and public); companies producing vaccines (if the vaccines are a success, in terms of effectiveness and then sales)10 or antiviral drugs; companies in the sector Media/Entertainment (due to a higher number of people housebound); possibly even delivery companies (for the same reason as the previous group), to name but a few.11 However, whether or not the spread of the virus was a deliberate deed still remains a mystery.
2.3.2. Mental health during and after the pandemic
As noted by Gunnell et al., “There is some evidence that deaths by suicide increased in the USA during the 1918–19 influenza pandemic and among older people in Hong Kong during the 2003 severe acute respiratory syndrome (SARS) epidemic.” (Gunnell et al.
2020, s. 468) They go on to mention: “The likely adverse effects of the pandemic on people with mental illness, and on population mental health in general, might be exacerbated by fear, self-isolation, and physical distancing.” (Gunnell et al. 2020, s. 470) The authors warn of a potential increase in mental health issues and suicide rates, especially as the pandemic and the subsequent financial pressures on individuals evolve.
(Gunnell et al. 2020, s. 470) Although the data on suicide rates are not available yet, the current pandemic is likely to have a negative social impact in terms of mental health.
10 This approach of focusing on effectiveness (in terms of defending against the SARS-CoV-2) and sales might yield unexpected adverse results in the form of side effects of the vaccine. We are witnessing a race for the first successful vaccine and the short periods of testing are raising doubts about its safety. According to the British portal Mail Online, “Professor Alexander Chucalin quit the Russian health ministry‘s ethics council” and “He specifically accused the two leading medics involved in its development of flouting medical ethics in rushing the vaccine into production.” (Stewart 2020) Whether this news is biased or not, there is no doubt about the necessity to test the vaccines thoroughly.
11 To continue with the example of companies producing vaccines, Dr. Judy Mikovits asserts herself in a short video called “Plandemic” (designed to suggest the words plan + pandemic), and she delivers the message that patenting the vaccines and selling them to uneducated public is a well-functioning business model (with potentially harmful health effects). She names a few people and points out to a possible conflict of interests: if the owner of the vaccine is in a position to give advice on public health. (Mikovits a Willis 2020)
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With reference to the expected outcomes of the COVID-19 in the area of mental health, Patrick Devitt analyses in his article “Can we expect an increased suicide rate due to Covid-19?” the effects of war and violence, natural disasters, epidemics/pandemics, and economic recessions/depressions on suicide rates. (Devitt 2020) The author searches for similarities between the current pandemic and the mentioned types of disasters to draw conclusions about the potential impact on mental health of population. With regards to this kind of impact, he states: “Of all the types of disasters – war, violence, natural disasters, epidemics/pandemics and economic recession – it appears that the most toxic is that of economic recession.” (Devitt 2020) Since the current and further expected economic slowdown is apparent, as documented in the section Economic impact, we are likely to witness a rise in the spectrum of mental health problems, including suicides. In addition, Devitt notes: “Particularly vulnerable groups include healthcare workers, the elderly and those who suffer crushing economic adversity.” (Devitt 2020, s. 4)
Now for the impact of economic recession, a study called “Impact of Business Cycles on US suicide rates, 1928-2007” provides acknowledgement of the relationship between economic recessions and suicide rates. (Luo et al. 2011) The authors Luo et al. show that there was a negative relationship between suicide rate and economic situation in the USA for most age groups (see Picture 5): “Graphical analyses showed that the overall suicide rate generally rose during recessions and fell during expansions.” (Luo et al. 2011, s. 1139) Therefore, the severity of economic recession connected to the coronavirus pandemic might have an impact on the number of suicides, this adverse extreme of social behavior. Only time will tell if the current crisis has been comparable in its extreme social impact (in terms of suicide rate) to the Great Depression. The authors of the study document that the increase in suicide rate in the USA from 1928 to 1932 was 22,8 % (reaching 22,1 deaths by suicide per 100 000 people in 1932), the highest 4-year increase in the whole period of the study: from 1928 to 2007. (Luo et al. 2011)
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Picture 5
Source: (Luo et al. 2011)
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2.3.3. Other fields under the impact of the pandemic
There are also fields of society that benefited from the current pandemic: such as attitude towards environment; family; and local communities, to name but a few.
First, there are visible signs in the environment that manifest that halt or slowdown of production proved to be advantageous to nature. An improvement in the quality of air and water has been documented in numerous areas. To illustrate, Saadat et al. provide the following information (in their paper from 2 August 2020): “Compared to this time last year, levels of air pollution in New York have dropped at almost 50% due to measures that have been to restrict the spread of virus.” (Saadat et al. 2020, s. 4) They also provide pictures of notable air quality improvement from some of the largest cities in the world.
The authors mention that water quality has improved too, pointing to cleaner water in canals of Venice. (Saadat et al. 2020, s. 5) This may lead people to consider the necessity of caring for their environment.
Second, families are spending more time together. Due to lockdown in some cities or areas, people have been made to stay home (either to work from home, or to cover quarantine period). This could be beneficial for the relationships in the family, as the hectic life full of work could often hinder families from enjoying quality time together.
Third, local communities provided a sense of communion among its members during this situation of hardship. Older people, who are more vulnerable and at risk of having serious symptoms due to weaker immune system in general, have been offered help of getting the groceries. Another example, which I have experienced, is sharing books in blocks of flats between neighbors (to substitute the services of local libraries, which were closed).
All in all, the COVID-19 pandemic imposed new regulations and unusual measures, which inevitably brought some improvements in our way of life. For instance, it made people experience the benefits of protection of the environment, focus more on family life, and empathize with their neighbors.
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To conclude, the root of the outbreak of the SARS-CoV-2 remains unknown.
Nevertheless, social impact of the spread of the virus in terms of fear, anxiety, and altered social behavior is notable and might have profound psychological consequences for the society. On the other hand, individuals have been able to experience more intensely the positive effects of time spent with closest family and neighbors, or the regeneration of environment.
2.4. Final remarks on the impact of the COVID-19 pandemic
Forecasts and models based on historical observations, such as the model in “The Global Macroeconomic Impacts of COVID-19: Seven Scenarios” (outlined in the section Forecasted economic impact) based on previous pandemics or the article “Impact of Business Cycles on US Suicide Rates, 1928–2007” (outlined in the section Mental Health during and after the pandemic) based on the relation between economic recessions and suicide rates, might draw a picture of how future might look like. However, as Taleb mentions: “We worry too late—ex post. Mistaking a naïve observation of the past as something definitive or representative of the future is the one and only cause of our inability to understand the Black Swan.” (Taleb 2010, s. 66) Therefore, comparisons with the previous pandemics, or other historical events, will probably not bear fruit. This pandemic is totally different than all the other pandemics before and will have a totally different, or literally unprecedented, consequences for the economy and society, whether it can be labelled a Black Swan event or not.
Another point made by Taleb that undermines our ability to forecast future is the presumption of rationality of subjects. When we try to predict something that is influenced by decisions of people12, it is necessary to take into account “free will” of subjects, which makes it virtually impossible to predict. (Taleb 2010, s. 197–198) As
12 Such as trying to predict the progression of a pandemic and its economic impact that is influenced by variables such as willingness to follow instructions of government, for example to wear a mask; stay at home; or distance socially (not mentioning variables that are unknown and have an effect). I also noticed a conflict between two seemingly “rational” approaches to battle the pandemic: is it rational of people in leading positions in government to enforce the necessity to stay at home on people until the virus disappears (rational in terms of global health) or to allow businesses to operate and people to go to work (rational in terms of reviving the economy as fast as possible)?
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Taleb highlights: “However, if you believe in free will you can’t truly believe in social science and economic projection. You cannot predict how people will act. Except, of course, if there is a trick, and that trick is the cord on which neoclassical economics is suspended. You simply assume that individuals will be rational in the future and thus act predictably. There is a strong link between rationality, predictability, and mathematical tractability.” (Taleb 2010, s. 198)
Regarding learning from the past, Taleb points to “the problem of induction.” He notes:
“Something has worked in the past, until—well, it unexpectedly no longer does, and what we have learned from the past turns out to be at best irrelevant or false, at worst viciously misleading.” (Taleb 2010, s. 65) Following picture (Picture 6) provides a very accurate illustration of this problem.
Picture 6
Source: (Taleb 2010, s. 65)
The graph in Picture 6 was used by Taleb to visualize the quality of life of a turkey in the period before and on Thanksgiving. This illustration can be applied to many other areas, such as value of a stock or probably even daily death toll during a pandemic. The development during the 999 days tells us nothing about the day 1000. (Taleb 2010, s. 66) Similarly, building forecasts based on past data can prove to be useless when the reality approaches. Therefore, forecasts of the effects of a pandemic (and forecasts in general)
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based on the development of previous pandemics (or other previous events) need to be regarded with caution. Additionally, even if a relationship pictured in a model repeated itself (such as the rise in suicide rates during economic recessions), we still do not know how many other variables (causing the suicide rates to rise or fall) we missed. This refers to the idea of Pierre-Daniel Huet, from his book Philosophical Treatise on the Weaknesses of the Human Mind, as Taleb puts it: “Huet presents arguments against causality that are quite potent—he states, for instance, that any event can have an infinity of possible causes.” (Taleb 2010, s. 71–72) Only God knows what the true causes of this pandemic situation are, and how large and diverse its impact on the society as a whole and its individual members will be. From my point of view, for its uniqueness, the COVID-19 pandemic may be regarded extreme in its impact, taking into account the following definition of “extreme” by the online portal Oxford Learner‘s Dictionaries:
“not ordinary or usual; serious or severe”. (Oxford Advanced Learner’s Dictionary 2020b)
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3. Comments on rarity and prospective unpredictability of the virus
3.1. Rarity
Rarity, for the sake of judging the criterion for a Black Swan event, might be understood in quite a few different ways. To begin, we can examine rarity of large outbreaks of viruses; in other words, it is possible to look at how often pandemic situations, similar to the current one in its international impact, take place. Then it is also viable to investigate how rare crises, such as the current economic; social; and health care crisis, are. Also, rarity of this particular type of virus, SARS-COV-2, might be taken into consideration.
Thoughts on these three different versions of the term “rarity” will be presented in the next sections.
3.1.1. Rarity of pandemic situations
The outbreak of coronavirus was declared a pandemic by the World Health Organization (WHO) on 11 March 2020. (Wikipedia 2020d) The question is, then, how rare pandemics are. Are pandemics rare enough to be labelled Black Swan events or have they become a common part of the current era, or even a common part of human history? To form a picture of the situation, comments regarding pandemics from two articles will be brought to reader’s attention.
In the first place, Kelly provides a definition for a pandemic: “A pandemic is defined as
‘an epidemic occurring worldwide, or over a very wide area, crossing international boundaries and usually affecting a large number of people’. The classical definition includes nothing about population immunity, virology or disease severity. By this definition, pandemics can be said to occur annually in each of the temperate southern and northern hemispheres, given that seasonal epidemics cross international boundaries and affect a large number of people. However, seasonal epidemics are not considered pandemics.” (Kelly 2011, s. 1) Since the coronavirus disease does not belong to the group of seasonal epidemics, it can be inferred that pandemics (like the current one) happen less than annually, perhaps not so often.
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Next, Cirillo and Taleb base their article “Tail risk of contagious diseases” on a collection of 72 pandemics, noting that: “[They] examine the distribution of fatalities from major pandemics in history (spanning about 2,500 years), and build a statistical picture of their tail properties.” (Cirillo a Taleb 2020, s. 1) Hence it might be deduced from the number of statistically comparable pandemics in the mentioned time frame that pandemics broke out on quite a few occasions to be reckoned rare events.
Accordingly, I deem the event of contemporary pandemic outbreak not satisfactory vis- à-vis the condition of rarity typical to a Black Swan event formulated by Taleb: “. . . it lies outside the realm of regular expectations, because nothing in the past can convincingly point to its possibility.” (Taleb 2010, s. 17)
3.1.2. Are crises (such as the current pandemic crisis) rare?
According to the portal Oxford Learner’s Dictionaries, crisis is “a time of great danger, difficulty or doubt when problems must be solved or important decisions must be made.“
(Oxford Advanced Learner’s Dictionary 2020a) Taking into account this definition, crises are not uncommonly occurring events. Whether we look at the global financial crisis or the current pandemic crisis, crisis is a time when difficulties come up and must be solved, which has extreme and uncommon impact on the functioning of the society. For reference, Roubini and Mihn comment on crises: “Crises, we argue, are neither the freak events that modern economics has made them seem nor the rare ‘black swans‘ that other commentators have made them out to be. Rather, they are commonplace and relatively easy to foresee and to comprehend. Call them white swans.” (Roubini a Mihm 2010, s. 6) If we look at the coronavirus pandemic from this point of view: as at just another difficulty causing a crisis, it is not a rare event at all. The fact that we have relatively often witnessed and probably will witness crises truly seems to be conceivable and crises might be regarded “white swans;” since on the one hand, they have an extreme impact, but on the other hand, they are not rare and might be expected.
3.1.3. Rarity of the virus
As mentioned in the previous chapter The extreme impact of coronavirus, the coronavirus disease, responsible for the current pandemic situation, is caused by the SARS-COV-2, or severe acute respiratory syndrome coronavirus 2. (Wikipedia 2020j) The rarity of the
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virus will be reviewed with reference to occurrence of the virus in the past, occurrence of related coronaviruses in humans, and occurrence of related coronaviruses in animals.
Firstly, the occurrence of the virus in the past needs to be considered. The fact that the strain of virus (in other words: the particular type of virus) causing the coronavirus disease responsible for the current pandemic was given a specific name, namely SARS-COV-2, validates that this strain of virus has occurred never before and is a brand new type of virus. Therefore, it might be asserted that this particular type of virus is rare.
Secondly, we have to go over the occurrence of related coronaviruses (in general) in humans. So far, only the SARS-COV-1 is documented to have caused an outbreak in human population. (Wikipedia 2020j) As a result, we may affirm that the occurrence of related coronaviruses in humans is relatively rare too.
Thirdly, the occurrence of related coronaviruses in animals needs to be looked over. There is evidence that other strains or types of coronaviruses (related to SARS-COV-2) are present in bats and palm civets (Wikipedia 2020j), which manifests that the occurrence of coronaviruses is not rare in nature.
To conclude, after researching the occurrence of the virus in the past; the occurrence of related coronaviruses in humans; and the occurrence of related coronaviruses in animals, it is plausible to claim that the emergence of a particular type of coronavirus (such as SARS-COV-2) is not a rarely occurring event, given the mutation of viruses that takes place in the natural environment.
3.2. Prospective unpredictability of the virus
To clear the heading up, prospective unpredictability of the immense impact of the virus will be tested.
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3.2.1. An approach based on reference
To prove that the pandemic was predictable is similar to proving that black swans exist.
One black swan spotted in Australia was enough to prove that they exist, and that it is not true that all swans are white.13 (Taleb 2010, s. 17) In like manner, one reference to a potential outbreak of a pandemic is enough to prove that somebody predicted it, and that it is not true that this pandemic was prospectively unpredictable. To illustrate that there were people who anticipated a pandemic, five references to an outbreak of a pandemic will be presented.
First, the WHO constructed a list of pathogens (see Picture 7) in 2016 that the organization called “diseases to be urgently addressed under R&D, as of May 2016.”
(WHO 2016) This list includes an item that went by the name: “Highly pathogenic emerging coronaviruses relevant to humans (MERS Co-V & SARS).” (WHO 2018; 2016;
Wikipedia 2020j) This provides a proof that the WHO considered the possibility of a serious health threat and even linked it to the right family of viruses: Coronaviridae (or Coronavirus). (Wikipedia 2020c)
13 See a picture of a black swan (Cygnus atratus) taken in Australia by John Harrison in Figure C (in List of figures at the end of this paper).
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Picture 7
Source: (WHO 2016)
Second, Bill Gates warns the public in his TED Talk in 2015 that the world is not ready for a pandemic. He predicts that something highly contagious would probably spread over the whole world, had it the severity compared to 1918 Pandemic. Gates even points out that the pandemic could have a natural cause or be a result of bioterrorism. (Gates 2015)
