Preview

Voprosy statistiki

Advanced search

What Do the Dynamics of the Coronavirus Pandemic in the «Large Economies» Have in Common?

https://doi.org/10.34023/2313-6383-2023-30-3-64-79

Abstract

The authors analyze the dynamics of infected and deceased from the coronavirus pandemic over 148 weeks in the «large economies» (24 countries). According to the authors, a large economy is a country that, at least within one year from 1980 to 2019, produced more than 1% of the global GDP. Although the organization of the health care system in these countries is different, only the general requirements of WHO could provide information on the spread of the pandemic in comparable formats. The change from daily data on the number of infected and deceased to weekly data on these indicators (per 1 million persons of the country's population) made it possible, firstly, to exclude insignificant daily fluctuations of these indicators and, secondly, to obtain information in comparable values for countries with widely differing populations.

The paper demonstrates that the frequently used comparison of countries by such integral indicators as the number of infected and deceased at a particular time is not very informative. It is due to the fact that, over time, country-specific circumstances change dramatically. Nevertheless, it was precisely the introduction for analytical purposes of such characteristics as weekly increment peaks of infected people and weekly increment peaks of deceased that made it possible to identify the four features. First, the number of those peaks is small for all countries: from 5 to 9 over 148 weeks. Second, these peaks cover between 70 and 90 percent of the totals of the integral number of infected and deceased in a given country. Third, most peaks of the infected are accompanied by peaks of the deceased with some delay: from zero to six weeks, but in most cases by two weeks, which is consistent with clinical observations. Fourth, the peaks of infected people in all 24 countries exhibit the statistical property of being quasi-synchronous (the so-called property of the maximums of these peaks to fall within predetermined intervals of weeks with probabilities that are the same for all countries). This fact is proved using the mathematical homogeneity criterion χ2.

About the Authors

V. M. Chetverikov
National Research University Higher School of Economics (HSE University)
Russian Federation

Victor M.  – Dr. Sci. (Phys.-Math.), Professor, School of Applied Mathematics, HSE Tikhonov Moscow Institute of Electronics and Mathematics

34, Tallinskaya Str., Room 422, Moscow, 12345



O. V. Pugacheva
Francisk Skorina Gomel State University
Belarus

Olga V. Pugacheva – Cand. Sci. (Econ.), Associate Professor, Department of Economic Informatics, Accounting and Commerce

104, Sovetskaya Str., Gomel, 246019



T. D. Vorontsova
National Research University Higher School of Economics (HSE University)
Russian Federation

Tatyana D. Vorontsova – Lecturer, School of Applied Mathematics, HSE Tikhonov Moscow Institute of Electronics and Mathematics

34, Tallinskaya Str., Room 901, Moscow, 123458



References

1. Kurkin А.А., Kurkina О.Е., Pelinovsky E.N. Logistic Models of Epidemic Growth. Transactions of NNSTU n.a.R.Е. Alekseev. 2020;2(129):9–18. (In Russ.)

2. Kokoulina М.V. et al. Analysis of Coronavirus Dyna mics Using the Generalized Logistic. Transactions of NNSTU n.a. R.Е. Alekseev. 2020;3(130):28–41. (In Russ.)

3. Pelinovsky E. et al. Logistic Equation and COVID-19. Chaos, Solitons & Fractals. 2020;140(1). Article 110241.

4. Pelinovsky E. et al. Gompertz Model in COVID-19 Spreading Simulation. Chaos, Solitons & Fractals. 2022; 154(1). Article 111699.

5. Danilova I.A. Morbidity and Mortality from COVID-19. The Problem of Data Comparability. Demographic Review. 2020;7(1):6–26. (In Russ.) Available from: https://doi.org/10.17323/demreview.v7i1.10818.

6. Kolosnitsyna M.G., Chubarov M.Yu. Spread of COVID-19 in the Russian Regions in 2020: Factors of Excess Mortality. Population and Economics. 2022;6(4):1–20. (In Russ.) Available from: https://doi.org/10.3897/popecon.6.e87739.

7. Chetverikov V.M. The Relationship Between the Current Account Balance and Growth Rates for Large Economies. Voprosy Statistiki. 2018;25(5):62–69. (In Russ.)

8. Chetverikov V.M. Unique Features and Intensity of Covid-19 Spread in Large Economies. Voprosy Statistiki. 2020;27(6):86–104. (In Russ.)

9. Chetverikov V.M., Pugacheva O.V., Vorontsova T.D. Challenges to Generating Reliable COVID Statistics: Domestic and International Experience. Voprosy Statistiki. 2021;28(4): 45–66. (In Russ.)

10. Rothan H., Siddappa N. The Epidemiology and Pathogenesis of Coronavirus Disease (COVID-19) Outbreak. Journal of Autoimmunity. 2020;109:102433. Available from: https://doi.org/10.1016/j.jaut.2020.102433; https://www.researchgate.net/publication/339515532_The_epidemiology_and_pathogenesis_of_coronavirus_disease_COVID-19_outbreak.

11. Husain I., Bauddha Sh. The Outbreak, Epidemic and Pandemic of Coronavirus Disease (COVID-19). International Journal of Advanced Research. 2021;8(8):80–88. Available from: http://dx.doi.org/10.22192/ ijarbs.2021.08.08.009; https://www.researchgate.net/publication/354199825.

12. Li Q. et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia. The New England Journal of Medicine. 2020;382(13):1199– 1207. Available from: https://doi.org/10.1056/NEJMoa2001316.

13. Ivchenko G.I., Medvedev Ju.I. Mathematical Statistics: Textbook. Мoscow: «Librokom» Publ.; 2014. 352 p. (In Russ.)

14. Bandoy D.J.D.R., Weimer B.C. Analysis of SARS-CoV-2 Genomic Epidemiology Reveals Disease Transmission Coupled to Variant Emergence and Allelic Variation. Scientific Reports. 2021;11(1). Articlenumber: 7380.

15. Chizhevsky A.L. Earth Echo of Solar Storms. Ed. 2nd. Moscow: Mysl' Publ.; 1976. 367 p. (In Russ.)

16. Chizhevsky A.L. Electrical and Magnetic Properties of Erythrocytes. Kiev: Naukova Dumka; 1973. 94 p. (In Russ.)


Review

For citations:


Chetverikov V.M., Pugacheva O.V., Vorontsova T.D. What Do the Dynamics of the Coronavirus Pandemic in the «Large Economies» Have in Common? Voprosy statistiki. 2023;30(3):64-79. (In Russ.) https://doi.org/10.34023/2313-6383-2023-30-3-64-79

Views: 256


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2313-6383 (Print)
ISSN 2658-5499 (Online)