Date of publication 13.09.2020



1.1. Analysis of the COVID-19 pandemic territorial unevenness in the European countries

1.2. Analysis of the European population mobility during the COVID-19 pandemic



3.1. Regularity of contagious disease pandemic occurrence

3.2. New tendencies in world economy and market sectors whose freefall and development are affected by the COVID-19 pandemic

3.2.1. Negative consequences

3.2.2. New opportunities





The analysis and study of the features of the spread of the COVID-19 coronavirus pandemic in European countries is rerformed. The research based on the territorial unevenness of the localization of the disease, the increased pedestrian and car mobility of people, the decreased level of social discipline of the population of different countries and other factors. The regularities of the cyclical occurrence of pandemics of infectious diseases were studied using the examples of successive emergence of four pandemics in the early 21st century: coronavirus SARS-CoV, swine flu, Ebola and coronavirus COVID-19 (SARS-CoV-2) which occurred over the past 18 years. Their impact on the development of the world economy and global society was studied. The negative consequences of the impact of the COVID-19 pandemic on the global economy and international business are analyzed. It is indicated that there are significant territorial risks as a result of the high concentration of production capacities and supply channels in some Asian countries, which puts international business in a dependent position. An attempt has been made to predict the transformation of the World and Europe after the end of the COVID-19 pandemic. Emphasis is placed on the fact that the pandemic will destroy the old sectors of the economy, which are based on low-skilled labor and low technology. Six new sectors of the world economy that mihgt be in demand by the world community and that may have a rapid development are analyzed. New opportunities have been discovered for some sectors of the world economy, which have received a significant impetus for development over the past 5-6 months, based on the new demands of people and business, in particular in the organic food industry, in teleworking technologies, in medical diagnostics, distance learning and distance bussiness and other areas.

Keywords: The COVID-19 pandemic, Nikolai Kondratiev’s 40-50 year economic cycles, Clement Juglar’s 7-11 year cycles, Dow Jones index, distance bussiness, transformation of the world economy


1.1. Analysis of the COVID-19 pandemic territorial unevenness in the European countries

From the territorial standpoint, the COVID-19 pandemic in the European countries started from the territory of the Northern Italy where several focuses of the virus spread had been formed in Lombardy region. From there, the virus began to rapidly spread to other, primarily neighboring Central European countries – France, Spain, Germany, and then, with a time lag of 2-3 weeks, to Eastern Europe and the Balkans – Poland, Romania, Ukraine, Croatia, Serbia, Slovenia, Montenegro and others.
In terms of the macro-regionalization of Europe, based on the UN regional classification and the peculiarities of the COVID-19 territorial spread [1], a series of maps showing changes in epidemiological parameters as of March 1, 2020, July 14, 2020 and September 11, 2020, was compiled (Fig. 1-5) [2].

Figure 1. Reported cases of the coronavirus infection as on 01/03/2020

Figure 2. Reported cases of the coronavirus infection as on 14/07/2020

Figure 3. Reported cases of the coronavirus infection as on 11/09/2020

а). Coronavirus infectionAt the beginning of the pandemic in Europe, the first suffered countries were Italy, Spain, France, and Germany that had the largest number of business, trade, and transportation contacts both with China and with each other. Later, the situation in the European Union began to develop under different scenarios depending on the readiness of the medical system, legislation and quarantine restrictions.

Eastern European countries and the Balkan countries were onto a good thing to proceed to a controlled morbidity process; hence, they passed this stage with a relatively low morbidity. The situation remained relatively stable in the Scandinavian countries, where a combination of factors of high household culture and social discipline, high level of health care and living standards contributed to the low number of patients.

Sweden was the exception in this macro-region; it used its own special approach to counteracting the pandemic. Under the leadership of the country's principal epidemiologist, Dr. Anders Tegnell, Sweden betook to mild but rational restrictions given the need to preserve its own economy and rapidly develop its collective immunity [3]. As a result, a monotonous increase in the number of sick people was observed in Sweden from the beginning of April to the end of July 2020, with a sharp peak in July, and since August and until now there is a drastic fall in the number of infected persons in the country (Fig. 4).

Figure 4. Covid-19 spread in Sweden compared with the EU countries, United Kingdom, France and Spain

The COVID-19 spread in the Russian Federation began later, however, at a fairly high rate, and in mid-May 2020, in terms of the total number of patients, the RF came out on top in Europe. (Fig. 2,3).

Since the end of August, a second wave of the pandemic is observed in Europe, which is characterized by increase in the daily dynamics of new cases in the Western Europe: Spain, France, and a rapid increase in the number of patients in Central and Eastern Europe, the Caucasus. It proves ineffectiveness of quarantine restrictions in Europe and Ukraine compared to the Swedish approach, as an example.

Figure 5. Relative number of reported cases as on 14/07/2020 (number of cases per 100,000 population)

Figure 6. Relative number of reported cases as on 11/09/2020 (number of cases per 100,000 population)

The distribution of the relative number of cases per 100,000 persons (Fig. 5,6) shows that the group of countries with a total number of cases exceeding 1,000 per 100,000 population includes Moldova, Luxembourg, Spain, Armenia, Andorra and San Marino. (Fig. 6), i.e., the European countries with small population.

The comparative dynamics for the region of Eastern Europe and the CIS countries, including Russia, Ukraine, Belarus, Moldova and Kazakhstan, shows a significant gap in the number of the sick between Russia and other countries, due to large population, intensive humanitarian and economic exchange with China and lack of rational quarantine measures in the early stages of the pandemic. The onset of the second wave of the disease complicates the situation in all countries of the region. The situation is deteriorating particularly rapid in Ukraine; in terms of the number of cases it is ahead of Belarus and Kazakhstan where some stabilization is observed in the number of new cases (Fig. 7).

Figure 7. Morbidity dynamics in the East European countries

Figure 8. Morbidity dynamics in different countries of Central Europe

In the region of Western Europe, let’s consider Italy, France, Spain, Great Britain, Germany. After a rapid increase in the number of sick patients in the spring of 2020, these countries reached the plateau in May. After that, from August 2020, the growth of new cases began again, especially in Spain and France. Great Britain and Germany prevent a sharp increase in new cases. Italy also continues to keep control of the situation (Fig. 9).

Figure 9. Morbidity dynamics in different countries of Western Europe

б). Mortality caused by COVID-19 pandemic. Mortality caused by COVID-19 pandemic both in Europe and the world was not high at the beginning of March. Deaths were reported mainly in Italy and France (Fig. 10). However, in two-three weeks the mortality began to grow exponentially. Consequently, the number of deaths in Italy, Spain, France, and Benelux countries varied between 10 and 50 thousand. It may be caused by population structure, when the aged form a relatively high per cent of the general population and the lifespan is long. The other reason of high mortality is a loss of time at the beginning of the pandemic. In the case of Great Britain and Germany, absolute indexes depend on general population size of the countries, when the density of population in agglomerations is very high. Russia with 18,000 deaths is also approaching the countries with a high mortality rate (Fig. 10, 12).

However, in Europe as a whole, statistics shows a decrease in the death rate from coronavirus. Recently, it equaled about 1.2% of the total number of cases. And 88% of all deaths occur among people aged 65 and older.

Figure 10. Deaths caused by COVID-19 as on 01/03/2020

Figure 11. Deaths caused by COVID-19 as on 14/07/2020

Figure 12. Deaths caused by COVID-19 as on 11/09/2020

In the group of Eastern European countries, Ukraine's indicators are deteriorating quite rapidly, with the number of deaths exceeding 3,000. The number of cases in other countries of the region is also growing (Fig.13).

Figure 13. Mortality dynamics in Eastern European countries

In Central Europe, the situation in Romania, Poland and Bulgaria is deteriorating rapidly (Fig. 14).

Figure 14. Mortality dynamics in Eastern European countries

Western European countries, after a difficult spring period of pandemic growth and increasing number of deaths, have managed to normalize this tendency and prepare their hospitals for effective treatment of patients and prevention of deaths (Fig.15).

Figure 15. Mortality dynamics in Western European countries

в). Recuperation from coronavirus. The total number of recovered persons in European countries is exactly proportional to the number of sick persons (Fig. 16). In the countries that hit the plateau earlier, the number of recovered persons was permanently high. Statistically high number of recovered persons is observed in Russia, Turkey, Central European countries, except France, and Spain. (Fig. 16,17).

With the onset of the second wave of disease, the number of active cases far exceeds the number of those who recovered in Spain, France, Great Britain, Sweden, and Greece. As in July, Ukraine belongs to the group of countries with a high percentage of simultaneously ill patients. Germany, Turkey, Finland and Iceland have a relatively low percentage of recovering cases (Fig. 18,19).

Figure 16. Number of persons recovered from COVID-19 as on 14/07/2020

Figure 17. Number of persons recovered from COVID-19 as on 11/09/2020

Figure 18. Ratio of recovered persons and confirmed morbidity cases as on 14/07/2020 (per cent)

Figure 19. Ratio of recovered persons and confirmed morbidity cases as on 12/09/2020 (per cent)

The absolute number of recoveries is also the largest in Russia, but if we consider the countries of the region except for it, the largest increase in the recovery shows Kazakhstan and Belarus (Fig. 20).

Figure 20. Recovery dynamics in Eastern European countries

Among the countries of Central Europe, Poland shows the best dynamics of recovery. Romania is in second place. Bulgaria also has a relatively high recovery growth rate (Fig. 21).

Figure 21. Recovery dynamics in different countries of Central Europe

In Western Europe, Germany shows the best recovery dynamics, hence, it is ahead of Italy. There are no leaps in the recovery of patients in France (Fig. 22).

Figure 22. Recovery dynamics in Western European countries

1.2. Analysis of European population mobility during the COVID-19 pandemic

Basing on the open data about the mobility of population in different countries of the world during COVID-19 pandemic period presented by the Apple company [4] the comparative study of the change in dynamics of walking and driving mobility of population of the European countries was performed (Fig. 23). The data correspond to human mobility in different countries and world regions shown on Apple Maps compared with respective indexes as on the basic date, January 13, 2020. The data are sent from devices of the Apple map service users and represent only the part of population that uses the Company’s devices and services. Hence, these data do not represent the behavior of population as a whole, but this estimate of change in human mobility dynamics is important enough.

We can see in Fig. 23 that severe quarantine measures taken at the beginning of March 2020, resulted in considerable decrease in mobility of population in the majority of European countries. Meanwhile, the gradual quarantine easement that began from the middle May 2020 gave rise to the tendency of human mobility growth.

Figure 23Change in dynamics of European population mobility during the quarantine time

Walking mobility in Italy and Spain dramatically increased during weekends and the summer recreation season, which resulted in human contacts growth and fast spread of the coronavirus among the population of these countries during the latent period. With the beginning of the quarantine in Italy and Spain the mobility dropped sharply to 10% from the beginning of the year. Due to strict observance of quarantine measures these countries succeeded in establishing control over the situation for a certain period and began to mitigate quarantine measures from the middle May.

Sweden didn’t implement large-scale quarantine measures and kept high mobility level all the time; the only difference was that weekend peaks were not too expressive. Despite the official quarantine measures the population of Ukraine kept fairy high mobility which was far beyond that of neighboring Poland and Romania where the mobility level dropped to 30-40% from the beginning of the year. With the beginning of the quarantine easement the human mobility in Ukraine rapidly increased and became comparable with Swedish dynamics.

Mobility diagrams (Fig. 23) clearly indicate the onset of the second wave of the morbidity in European countries. This is especially true in Spain, where there is the greatest increase in new cases. The population of Ukraine reacts weakly to the sharp increase in new cases in Ukraine, which has a negative impact on the epidemiological situation.


In view of the fact that it is incorrect to estimate the impact of COVID-19 pandemic on economy and social processes in any country basing on one index only (for example, on the number of morbidity cases per 1000 persons), we shall study the character of the sickness spread using the set of the most important indexes. Basing on the findings of the study we shall combine countries in groups (clusters) by the criterion of their maximum similarity in terms of these indexes. With this purpose we shall use the method of correlation-regression analysis in order to compare principle indexes of the disease spread in the European countries, and the method of cluster analysis to determine the groups of countries, as well.

The following indexes of the disease spread were taken into consideration: 

  • Number of COVID-19 reported cases per day (P1);
  • Number of COVID-19 reported deaths per day (P2);
  • Number of reported recuperations from COVID-19 per day (P3);
  • Mobility index (P4);
  • Population size (P5);
  • Density of population (P6);
  • Number of performed tests per 1000 persons (P7).

Cross-correlation coefficients , were calculated for indexes P1 - P4 for 37 countries of Europe, and indexes P5 - Pfor the i-th country were normalized within the range 0 to 1 by minmax method: :

It is needed to find distances between the countries in the space of P1 –P7 indexes in order to perform the cluster analysis. Therefore, the values reciprocal to the correlation coefficients

and Euclidean distance

were used. Hence, we get the distance matrix.

Then, using the Distij distance matrix in the space of indexes P1 - P7, 6 clusters were formed with the help of the k-means and tools of the data processing language R [5] (Table 1, Fig. 24). According to the method used, the clustering was carried out in such a way that the sum of the distances from the center of the cluster to the countries was the smallest in the considered multidimensional space.

Table 1. Results of cluster analysis of the European countries in the system of P1 –P7 indexes.

Country Population (mln) Density of population Number of infected per 1000 persons Number of deaths per 1000 persons Mortality (% to the number of infected) Number of tests per 1000 persons Сluster
Slovakia 5,5 113,13 0,92 0,01 0,74 68,73 1
Greece 10,4 83,48 1,19 0,03 2,39 104,99 1
Slovenia 2,1 102,62 1,63 0,06 3,87 85,08 1
Poland 37,8 124,03 1,91 0,06 2,98 74,26 1
Czech Republic 10,7 137,18 3,03 0,04 1,38 94,72 1
Croatia 4,1 73,73 3,15 0,05 1,61 51,35 1
Serbia 6,8 80,29 4,72 0,11 2,27 148,34 1
Romania 19,2 85,13 5,18 0,21 4,08 106,14 1
Cyprus 0,9 127,66 1,73 0,02 1,38 258,72 2
Denmark 5,8 136,52 3,27 0,11 3,32 488,67 2
Belarus 9,4 46,86 7,79 0,08 0,99 169,91 2
Germany 83,8 237,02 3,07 0,11 3,64 160,37 3
Netherlands 17,1 508,54 4,58 0,36 7,96 106,94 3
Italy 60,5 205,86 4,68 0,59 12,57 96,24 3
United Kingdom 67,9 272,9 5,28 0,61 11,62 237,84 3
France 65,3 122,58 5,42 0,47 8,71 153,13 3
Belgium 11,6 375,56 7,81 0,86 10,96 218,42 3
Bulgaria 6,9 65,18 2,53 0,1 4,01 65,7 4
Ukraine 43,7 77,39 3,4 0,07 2,07 41,31 4
Albania 2,9 104,87 3,77 0,11 2,98 23,25 4
Bosnia and Herzegovina 3,3 68,5 6,87 0,21 3,02 61,72 4
Macedonia 2,1 82,6 7,34 0,3 4,15 78,3 4
Kosovo 1,9 168,16 7,47 0,3 4,02 NA 4
Moldova 4 123,66 10,34 0,27 2,65 52,22 4
Latvia 1,9 31,21 0,77 0,02 2,42 145,7 5
Hungary 9,7 108,04 1,05 0,07 6,18 53,54 5
Lithuania 2,7 45,14 1,18 0,03 2,69 252,4 5
Finland 5,5 18,14 1,53 0,06 3,98 142,46 5
Estonia 1,3 31,03 1,96 0,05 2,46 126,43 5
Norway 5,4 14,46 2,17 0,05 2,26 154,62 5
Austria 9 106,75 3,52 0,08 2,36 146,21 5
Switzerland 8,7 214,24 5,27 0,2 3,81 134,29 5
Portugal 10,2 112,37 6,09 0,18 2,98 216,78 5
Ireland 4,9 69,87 6,15 0,36 5,87 189,62 5
Sweden 10,1 24,72 8,53 0,58 6,78 123,67 5
Spain 46,8 93,11 12,11 0,64 5,25 157,12 5
Russia 145,9 8,82 7,17 0,13 1,75 273,5 6


 Figure 24. Results of the cluster analysis of the European countries in the system of P1 –P7 indexes

Countries of the 1st cluster – Slovakia, Greece, Slovenia, Poland, Czech Republic, Croatia, Serbia, Romania, are characterized by a relatively low number of infected persons, low mortality and the medium level of tests performed. Fig. 25 shows the number of infected people growth in the countries of this cluster.

 Figure 25. Number of reported COVID-19 cases for the countries of the 1st cluster

The countries of the 2nd cluster – Cyprus, Denmark, Belarus, differ slightly in the intensity of the spread of the disease and the number of deaths from the group of countries in the first cluster. However, the number of tests conducted in these countries is one of the highest in Europe (excluding Belarus). Fig. 26 shows the graphs of spread of the COVID-19 pandemic in these countries.

Figure 26. Number of registered COVID-19 cases for the countries of the 2nd cluster

The group of countries of the 3rd cluster with a higher intensity of COVID-19 spread includes Germany, Netherlands, Italy, United Kingdom, France. These countries have the highest pandemic intensity in Europe, high mortality and a great number of tests per 1,000 people, as well as rather severe quarantine restrictions. As a result of the effective application of anti-epidemic measures, the disease in these countries quickly declined. Fig. 27 shows the number of patients with COVID-19 for the countries of this group.

Figure 27. Number of registered COVID-19 cases for the 3rd cluster of countries

Bulgaria, Ukraine, Albania, Bosnia and Herzegovina, Macedonia, Kosovo belong to the 4th cluster of countries with a COVID-19 prevalence above average. These countries are characterized by a relatively small number of tests performed. Fig. 28 shows the number of patients with COVID-19 in the countries of the 4th cluster.

Figure 28. Number of registered COVID-19 cases for countries of the 4th cluster

Countries of the 5th cluster – Latvia, Hungary, Lithuania, Finland, Estonia, Norway, Austria, Switzerland, Portugal, Ireland, Sweden, Spain, are characterized by relatively low disease spread, low mortality, and high number of tests performed. Fig. 29 shows diagrams of the disease spread in these countries.

Figure 29. Number of registered COVID-19 cases for countries of the 5th cluster

Russia is included in a separate 6th cluster. It demonstrates a relatively high pandemic rate, along with Belarus and Czech Republic, with a very low mortality rate and the highest rate of testing in Europe. Fig. 30 shows a diagram of the pandemic spread in Russia. For comparison, the same figure shows the corresponding characteristics for Spain.

Figure 30. Number of reported COVID-19 cases in Spain and Russia


3.1. Regularity of contagious disease pandemic occurrence

Wide-scale contagious diseases (pandemics) became more frequent during last two decades; they materially affect human health, social development, economy of countries and world regions.

  • Thus, from November 2002 to May 2004, the outbreak of severe acute respiratory syndrome (SARS) occurred in 35 countries around the world, caused by the previously unknown coronavirus SARS-CoV. A total of 8461 SARS cases were reported, of which 916 ended in death. The mortality rate was 10.83%.
  • From January 2009 to August 2010, most of countries of the world suffered from swine flu, which escalated into the H1N1 / 09 pandemic. From 700 million to 1.4 billion people suffered from the disease, 150 to 575 thousand people became its victims. The mortality rate did not exceed 1%.
  • In 2014-2015, West Africa, the United States, and Europe were affected by the Ebola pandemic, or the so-called hemorrhagic syndrome. The number of those infected with the Ebola virus was more than 9 thousand persons, 4450 of them died. The mortality rate was 50%.
  • The beginning of 2020 was sadly marked by the rapid and most widespread outbreak of the COVID-19 (SARS-CoV-2) coronavirus pandemic practically all over the world. As of mid-October 2020, there were about 29 million patients in the world, about 1 million people died. The world average mortality rate is around 3.5%.

It is seen that emergence of pandemics within the indicated time period is of cyclical nature with the emergence period of about five-six years. To analyze the impact of these pandemics on the global economy we shall compare them along the time axis with the following fundamental periodic processes:

  • Nikolai Kondtatiev’s 40-50-year economic cycles based on changes of technological structure of the society [6];
  • Clement Juglar’s 7 – 11-year cycles associated with fluctuations in the levels of capacity utilization and fluctuations in the volumes of investments in fixed capital (channeling investments in business) [7];
  • Dow Jones industrial average that reflects the general capitalization of 30 biggest American companies whose activities in total set the trend for the global economy [8].

Fig. 31 shows that within 2020-2021 period the descending wave of the Kondratiev’s 5th cycle comes to an end and then it switches to the ascending wave of the Kondratiev’s 6th cycle in the process of transition to the next technological mode. It demonstrates that objective conditions really exist for further long-term uprising of the world economy.

Note that the 5th technological cycle comprised a set of the following principal technologies: - microelectronics, Internet, computer technology, mechanical engineering, transport, energy, space technology and other technologies traditional for the second half of the 20th, early 21st century.

The sixth technological cycle began to emerge from the 10s of the 21st century. It continues to take shape up to this day. Its main technologies are life sciences, biomedical engineering, cell medicine, genetics, pharmacy, green energy, new substances and materials, nanotechnology, mobile information and computer technologies, network services, including Internet commerce, space services and travels.

Meanwhile, the intensity of such uprising of economy within the 2020-2021 time period is substantially weakened due to a break of traditional economic chains resulted from the COVID-19 pandemic, considerable dispersion (defocusing) of investments in different businesses (both outdated and prospective), that results in hitting another bottom of Juglar’s cycle and decreasing Dow Jones industrial average by 30-40%. According to Juglar, this recession will continue during, approximately, a year within which redirection of investments to the 6th cycle technologies takes place. Upon escalation of contribution into the global GDP over 5-7% due to the 6th cycle technologies the economic revival shall begin both according to Kondratiev and Juglar.

 Figure 31. Impact of contagious disease pandemics on the development of economy and society

3.2. New tendencies in world economy and market sectors whose downfall and development are affected by the COVID-19 pandemic

Global economic downfalls were observed at different historical times. At the beginning of the 21-th century they occurred, among other factors, under the impact of flu and swine flu pandemics in 2008-2009 and Ebola pandemic in 2014-2015. However, they had a very short-term impact on the global economy (several months to a year), and then the objective economic development continued with the elements of renewal and partial elimination of some artificial strata (financial bubbles, pyramids, etc.). While extrapolating the events of 2008-2009 and 2014-2015 to the actual situation with COVID-19 pandemic, we may formulate a foresight statement that the global economic downfall in 2020 will be deeper as compared with the aforesaid previous crises. However, just in the second half of 2021 – the beginning of 2022, upon new pandemic reduction and eradication of old and artificial strata, the global economy will begin to revive and grow in accordance with the aforesaid objective laws.

Fig. 32 shows the IMF data concerning global GDP dynamics affected by three above-described pandemics. We see that after the swine flu pandemic of 2008-2009 the global economy collapsed by 3.4% (from +1.7% growth to -1.7% decline), and after the Ebola pandemic of 2014-2015 it declined by 0.7%. Pursuant to the foresight of Munich Economic Institute Ifo made on the basis of interrogation of approximately 1000 experts from 110 countries, the GDP of the Eurozone in 2020 may decline by 5,3%, and the global GDP – about 2% [9].

Figure 32. Global GDP dynamics affected by three above-described pandemics

3.2.1. Negative consequences. Pandemic crisis affects the tendencies of international business development. Essential territorial risks arise because of high concentration of production facilities and supply chains in some Asian countries; hence, the international business becomes subordinated. By this reason, a diversification of supply chains will take place, as well as removal of certain production facilities from Asian territory to the countries with highly educated population, for example, Poland, Romania, Ukraine, Slovakia, etc.

During next 5-10 years all production and agricultural sectors will substantially decline, which are based on the technologies of the 5th cycle and lower, and have high concentration of employees that perform low-skilled operations. Thus, during the recent half-year travel agencies, transport, restaurants, entertainment and hospitality industry suffered from considerable losses, as well as a great number of industrial sectors (except agriculture).

For the first time since 2009 the global economy will demonstrate downturn [9]: After its growth by 2.5% in 2019, the global GDP in 2020 will decrease by 2% (Fig. 33), and this collapse will continue in the first half of 2021. The recession is expected on the markets of 68 countries, compared with 11 countries in the last year, the international trade volume will decrease by 4,3%, and the number of bankruptcies in the world will increase by 25%.

Figure 33. Estimates of the GDP growth in 2020 (World bank, average year values)

Even now consumers have passed into the severe saving mode and drastically reduced their commodity and services expenditures. Purchases of costly goods – domestic appliances, electronics, cars, housing accommodations, etc., are postponed.

Because of bankruptcies mainly in the sectors of small and medium business, on the one hand, and production automation and mechanization of agriculture, on the other hand, quick growth of unemployment is expected. According to analysts’ estimates the unemployment may grow by 15% in the world and 20% in Europe. These phenomena may cause severe social disorders because personnel retraining and creation of a great number of job positions in new sectors of economy will be very slow as compared to destructive processes of the previous economic cycle.

The given estimates may come true provided that the outburst of the coronavirus second wave will not occur in the third, fourth quarters of 2020, and most countries will not go back to the strict quarantine. If so, all estimates shall be adjusted for the worse.

The impact of the possible coronavirus second wave may be decisively lowered due to effective work of national healthcare systems which were mobilized during the first wave period. The data concerning readiness of healthcare systems in various countries of the Eastern Europe are represented in Fig. 34.

Figure 34. Index of readiness of healthcare systems to overcome COVID-19 pandemic consequences in the Eastern Europe countries

3.2.2. New opportunities. Pandemic crisis negatively affected practically all sectors of the global economy, however, some of them during recent 5-6 months received considerable impetus for their development, keeping in mind specific features of human and business actual needs. In its Future Possibilities Report 2020 [10], the United Nations Organization identifies six megatrends that will transform the world after the end of the COVID 19 pandemic. They are as follows:

1. The Big Data Economy: Hyper-connected Society

Against the background of the introduction of 5G technologies, cheaper and more efficient computing power and data storage, a breakthrough in the level of communication between people is expected. The ability to transmit ultra-large data streams, quickly analyze and process them using artificial intelligence will significantly improve the ability to optimize processes and services and create new, efficient business models in various areas of human activity.

In all branches of human activity, the development of artificial intelligence technologies, intelligent robots, sciences, and technologies for big-data processing is significantly accelerated in order to recognize the hidden patterns and other intelligent systems.

Distance work technologies in business, education, public services, medical diagnostics, some other spheres are developed at a rapid rate. During the half-year quarantine period the information-entertainment on-line services increase by 20% – 30%, on-line retail and courier delivery sector – by 40% – 60%, on-line educational and gaming platforms – by 40% – 50%, on-line webinar, teleconference and training platforms – by 60% – 70%, e-commerce – by 30% and pharmaceutical branch – by 40% – 60% [9].

According to UN estimates, Big Data Economy could grow to 8 trillion US dollars by 2025.

2. The Wellbeing Economy

Rethinking the fundamental values of human life, interest in physical and psychological well-being is already huge, and after the end of the pandemic, it will grow significantly. New approaches to improving people's living standards are rapidly being rethought and implemented at the individual, organizational and community levels. There are many new opportunities in this sector, especially in high-income countries. But middle-income and even low-income countries will follow in the footsteps of developed countries.

In the first instance, there will be a significant increase in the interest in rethinking human health, physical and psychological well-being. Health prevention, self-improvement training, organizational and educational programs, fitness, diet, health and beauty, travels and smart real estate will be in demand. In just six months of the COVID-19 pandemic spread, consumer demand for organic food in the European Union increased by an average of 6%, the production of electronics and special systems for medical and educational needs increased by 40% -50% [9].

The total value of this segment of the economy can reach 7 trillion US dollars in the space of a few years.

3. Low-Carbon Economy

Pursuant to the Paris Agreement, approved in December 2015 by the 21st session of the “COP21”, UN Climate Change Conference, 195 countries have committed to a gradual transition to a model of low-carbon economy. The purpose of this model implementation is to prevent an increase in the Earth’s temperature by 2 degrees, which according to experts is a threshold value, after which, irreversible processes in the ecology of the Planet will begin as a result of global warming.

The Paris Agreement became a new important reference point for the world economy. The growing demand of markets for energy must be met through the development of new, green energy. Even now, investment models and innovations in energy-saving technologies, fundamentally new battery technologies, electric transport, energy-efficient buildings, and fuel cells running on hydrogen are gaining special importance. Growing demand for renewable energy may form a segment of low-carbon economy of 2.3 trillion US dollars in the coming years.

4. The Circular Economy

Awareness of the world community about the need to reduce the negative impact of life-sustaining activities on the environment is becoming an important motivator for the development of a circular economy aimed at reusing resources and reducing wastes. The basis of this economy is the secondary resource potential. Even under crisis conditions of production during the pandemic, tens of billions of tons of wastes are generated in the world comprising more than 1,000 items. Mining, food, fuel and energy, metallurgy, chemical industry, and household wastes of the population of the Planet dominate in the waste profile.

The circular economy has formed a great demand for the creation of new, innovative technologies for the waste processing and disposal, and their reuse; such technologies will become more public-facing as new technological solutions emerge. Secondary metallurgy, technologies of utilization and secondary use of nuclear power plants waste, polymeric materials, wood, glass, metal and plastic containers and packaging are already gaining significant development.

According to UN experts, the use of the circular economy can open market opportunities in this area totaling up to 4.5 trillion US dollars.

5. The BioGrowth Economy

The COVID-19 pandemic gives a new impetus to the development of the biological growth economy, in particular, the organic food industry, precision farming technologies (based on satellite and unmanned monitoring systems, artificial intelligence systems, high level of mechanization), the creation of biomaterials with new quality characteristics. Rapid progress in the field of biomaterials, crop production and synthetic biology will lead to the creation of sustainable crops, processing of fuel from agricultural waste, the creation of substitutes for animal proteins, biological materials that decompose and do not exacerbate the waste problem.

By 2025, the volume of the biological growth economy can reach 1 trillion US dollars.

6. The Experience Economy

The experience economy is considered as the next link in the evolutionary chain: agricultural, industrial, service economy, experience economy. This form of economy retains ties between the need for goods that are generally useful or functional, with the need for goods that provide a positive individual experience, mental satisfaction, the desire of people for better “living standards”. In this economy, goods manufacturers add a “psychological stress” to basic products. This emotional component is associated with positive memories of consuming certain products, brands in the past, to which people are accustomed and loved them.

The product history becomes a significant part of what people buy. Experts call this trend the commercialization of emotions, when people buy mostly stories, legends, emotions and the way of life to which they are accustomed. With the rapid development of 3D printing, chatbots, virtual reality technologies, goods and services are increasingly becoming personalized, they give the consumer emotional, mental satisfaction, in addition to functional qualities. The experience economy is gradually spreading from elite markets to mass consumption markets. 

The experience economy is given a special impetus during the COVID-19 pandemic, when a special need exists to compensate for the negative psychological state caused by this disease, with a set of positive feelings, memories and emotions that can be provided to people by this economy. In particular, virtual tourism, 3D and 4D film industry, entertainment industry, social networks become especially popular. 

The experience economy can reach 6.5 trillion US dollars by 2025.


  1. At the initial stages of COVID-19 pandemic spread in Europe the most developed countries of Western Europe suffered the most because they had the most intensive business, commercial and transport contacts both with China and each other; such factors as vicinity to the pandemic focus in the Northern Italy, open borders, intensive transport communication, high density and mobility of population contributed to rapid and uncontrolled coronavirus spread.
  2. Certain time lag in pandemic spread allowed other European countries to implement quarantine measures and prepare themselves to counteract the disease. The best results were observed in the East European and Scandinavian countries (except Sweden). Swedish model of epidemic progress demonstrates greater number of cases as compared with neighboring countries.
  3. The ex-USSR countries also substantively suffered from the pandemic. Nonobservance or disregard of quarantine measures in Russia and Belarus resulted in high morbidity dynamics. In this, certain negative tendencies are also observed in Ukraine, notwithstanding the situation with mortality rate in the country is controlled. Existence of red danger level in neighboring countries creates additional risks for their neighbors.
  4. Analysis of the Severe Acute Respiratory Syndrome (SARS) caused by SARS-CoV coronavirus, swine flu, Ebola and COVID-19 pandemics (that took place during recent 18 years) impact on the global economy and community development demonstrated that these pandemics have a cyclical nature with the emergence period of about five-six years. They materially affect the global economy and result in severance of economic ties and deceleration of economy and society development for several months or even a year or two.
  5. To study COVID-19 pandemic impact on European countries the foresight mathematical model was developed, and computer modelling of the phenomenon was performed. Calculations made under pessimistic and optimistic scenarios allowed to estimate the scale of human losses and time horizons of COVID-19 pandemic rise and extinction in some European countries. The findings of the study may be used by national governments to work out a scenario aimed at pandemic prevention and implementation of remedial actions.
  6. Negative consequences of COVID-19 pandemic effect on global economy and international business were analyzed. It is found that substantial territorial risks appear due to high concentration of production facilities and supply chains in certain Asian countries, that makes the international business subordinate. Consequently, diversification of supply chains takes place, as well as transfer of some production facilities from the Asian territory to the countries with highly educated population such as Poland, Romania, Ukraine, Slovakia, etc.
  7. It is pointed out that during next 5-10 years most of production sectors will substantially decline, which are based on the technologies of the 5th cycle and lower and have high concentration of low-skilled employees. Thus, during the recent half-year travel agencies, transport, restaurants, entertainment and hospitality industry as a whole suffered from considerable losses, as well as a great number of industrial sectors (except agriculture).
  8. New opportunities are found for six sectors of the global economy which received a substantial impulse during recent 5-6 months for their development, in view of specific features of human and business demand now and soon. In particular, a growth is observed in the agrarian sector; in the organic food industry, in the distance work technologies in business, education, in the industry of virtual tourism and entertainment, in telemedicine diagnostics, in the field of artificial intelligence, intelligent robots, large data processing technologies and telecommunications, in green energy, in recycling systems and waste recycling.
  9. It is shown that during the quarantine, information-entertainment on-line services increased by 20% – 30%, on-line retail and courier delivery sector – by 40% – 60%, on-line educational and gaming platforms – by 40% – 50%, on-line webinar, teleconference and training platforms – by 60% – 70%, and pharmaceutical branch – by 40% – 60%. 


  1. Standard country or area codes for statistical use, UN Statistics Divisionhttps
  2. COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University
  3. Anders Tegnell and the Swedish Covid Еxperiment, FT, SEPTEMBER 11 2020
  4. Apple Company Report on data of the mobility trends, 2020
  5. R Documentation. K-Means Clustering
  6. Гринин Л. Е. Вербальная модель соотношения длинных кондратьевских волн и среднесрочных жюгляровских циклов // История и математика: Анализ и моделирование глобальной динамики. Ред. А. В. Коротаев, С. Ю. Малков, Л. Е. Гринин. М.: Либроком, 2010. С. 44-111.
  7. A Spectral Analysis of World GDP Dynamics: Kondratieff Waves, Kuznets Swings, Juglar and Kitchin Cycles in Global Economic Development, and the 2008–2009 Economic Crisis. Structure and Dynamics, 4(1).
  8. Dow Jones Industrial Average
  9. Impact of COVID-19 on the economy. COFACE analytical materials
  10. Future Possibilities Report, Unated Nationals Organization, 2020


Academic advisor: M.Z. Zgurovsky

Project Team: N.V. Gorban, B.R. Dudka, K.V. Yefremov, Yu.P. Zaychenko, P.O. Kasianov, O.P. Kupenko, M.M. Perestiuk, I.O. Pyshnograiev, V.V. Putrenko.

© World Data Center
    for Geoinformatics and Sustainable Development
    September 13, 2020