Abstract
This article discusses different-scale cycles of solar activity, from 11-year to quasi-millennial, and the manifestation of their combinatorics in epidemiological dynamics. It is shown that a significant change in the dynamics of the number of infectious diseases during an 11-year cycle is associated with solar activity, and not with its geophysical manifestations. Covid-19 pandemic paradoxes to began under conditions of a simultaneous minimum of 11-year solar activity (SA) and a minimum of the quasi-secular solar cycle are considered. It is assumed that under the conditions of the global SA minimum, genetic population characteristics played a decisive role in the development of local coronavirus epidemics, and also played a significant role in the effectiveness of mass vaccination in various countries. The highest relative mortality was observed in haplogroup R1b (values 20–35) versus values 5–8 in haplogroup R1a, and values 2–4 in haplogroup N. Vaccination efficiency is also maximum in haplogroup R1b. The estimated height of the cycles during which viral pandemics can develop both at the maximum and at the minimum of 11-year SA cycles fluctuates around the value of 100–110 average annual Wolf numbers. Basically, this binary phenomenon is observed in the phase of growth and decline of the SA quasi-centennial cycle. Under conditions of a long global minimum of solar activity with a cycle amplitude of 90 to 120, a doubling of the number of viral pandemics can be observed, with a significant contribution of the genetic characteristics of the population to the dynamics of local epidemics.
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ACKNOWLEDGMENTS
The author is deeply grateful to V.N. Obridko, E.G. Khramova, and A.V. Belov for helpful discussions.
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Appendices
APPENDIX 1
1.1 HAPLOGROUPS
The term “haplogroup” is widely used in population genetics and genetic genealogy, the science that studies the genetic history of humanity through haplogroup research on Y chromosomes (Y-DNA), mitochondrial DNA (mtDNA), and MHC haplogroups. A haplogroup is a group of similar haplotypesthat have a common ancestor who had mutation inherited by all descendants (usually a single nucleotide polymorphism). Y-DNA genetic markers are transmitted with the Y-chromosome exclusively through the paternal line (that is, from father to son), and mtDNA markers through the maternal line (from the mother to all her children). Thus, men are carriers of Y-DNA and mtDNA markers, while women are carriers of only mtDNA. Haplotypes for autosomal markers are present in both men and women. The characteristic times of the formation, divergence, and existence of haplogroups are thousands and tens of thousands of years.
Haplogroup R on the human Y chromosome is marked by a mutation in SNP marker M207 and is a descendant of haplogroup P (Y-DNA). In Europe, the most common subgroup R1 is marked with the M173 mutation. Its two main subclades R1a (M17) and R1b (M343) are the most common throughout Europe and Western Eurasia. This is due to migration during the last glacial maximum. Haplogroups R1a and R1b dispersed about 22 000 years ago in connection with the migration of peoples.
APPENDIX 2
A table of the population composition by haplogroups in European countries.
No. | Country | Population | R1a, % | R1b, % | N1c1, % | J1, % | J2, % | G2a3, % | I1, % | I2b, % | I2a, % | E1b1b1, % | T, % | Q, % |
1 | Russia (with Asian part) | 143 200 000 | 47.0 | 6.0 | 20.0 | 1.0 | 3.0 | 4.0 | 5.0 | 0.0 | 10.5 | 5.0 | 1.0 | 1.5 |
2 | Germany | 81 903 000 | 16.0 | 44.5 | 1.0 | 0.0 | 4.5 | 5.0 | 16.0 | 4.5 | 1.5 | 5.5 | 1.0 | 0.5 |
3 | France | 65 350 000 | 2.5 | 61.0 | 0.0 | 1.0 | 7.0 | 5.0 | 9.5 | 4.0 | 2.0 | 7.0 | 5.0 | 5.0 |
4 | Great Britain | 62 698 362 | 4.50 | 67.0 | 0.0 | 0.0 | 3.5 | 1.5 | 14.0 | 4.5 | 2.5 | 2.0 | 0.5 | 0.5 |
5 | Italy | 60 813 326 | 2.5 | 49.0 | 0.0 | 2.0 | 18.0 | 7.0 | 2.50 | 1.0 | 3.0 | 11.0 | 4.0 | 0.0 |
6 | Spain | 47 190 500 | 2.0 | 69.0 | 0.0 | 1.5 | 8.0 | 3.0 | 1.50 | 1.0 | 4.5 | 7.0 | 2.5 | 0.0 |
7 | Ukraine | 45 559 058 | 43.0 | 4.0 | 6.0 | 0.5 | 6.5 | 2.5 | 3.0 | 1.0 | 21.0 | 7.0 | 2.0 | 3.0 |
8 | Poland | 38 538 447 | 55.0 | 12.0 | 5.0 | 1.0 | 2.5 | 2.0 | 6.0 | 1.0 | 9.0 | 5.0 | 0.5 | 1.0 |
9 | Romania | 19 042 936 | 18.0 | 16.0 | 0.0 | 1.5 | 13.0 | 6.5 | 2.0 | 2.0 | 26.0 | 9.0 | 2.5 | 2.5 |
10 | Netherlands | 16 743 507 | 6.0 | 53.5 | 0.5 | 0.0 | 6.0 | 2.5 | 18.5 | 6.0 | 1.0 | 4.5 | 1.0 | 0.5 |
11 | Belgium | 11 071 483 | 4.0 | 61.0 | 0.0 | 1.0 | 4.0 | 4.0 | 12.0 | 4.5 | 3.0 | 5.0 | 1.0 | 0.5 |
12 | Greece | 10 787 690 | 11.5 | 15.5 | 0.0 | 3.0 | 23.0 | 6.5 | 3.5 | 1.5 | 9.5 | 21.0 | 4.5 | 0.0 |
13 | Portugal | 10 581 949 | 1.5 | 56.0 | 0.0 | 3.0 | 9.5 | 6.5 | 2.0 | 3.0 | 1.5 | 14.0 | 2.5 | 0.5 |
14 | Czech | 10 512 208 | 34.0 | 22.0 | 1.5 | 0.0 | 6.0 | 5.0 | 11.0 | 4.0 | 9.0 | 6.0 | 1.0 | 0.5 |
15 | Hungary | 10 014 324 | 32.5 | 17.0 | 1.5 | 0.0 | 7.0 | 5.0 | 8.0 | 2.5 | 15.0 | 9.5 | 1.0 | 1.0 |
16 | Sweden | 9 514 406 | 19.0 | 22.0 | 11.0 | 0.0 | 3.0 | 1.0 | 35.0 | 4.0 | 0.0 | 1.0 | 1.0 | 3.0 |
17 | Belarus | 9 465 400 | 49.0 | 10.0 | 10.0 | 0.0 | 1.5 | 1.0 | 3.0 | 1.0 | 18.0 | 5.0 | 1.5 | 1.0 |
18 | Austria | 8 460 390 | 23.0 | 26.0 | 0.0 | 0.0 | 12.0 | 8.0 | 12.0 | 2.0 | 6.0 | 9.0 | 1.0 | 0.5 |
19 | Switzerland | 8 000 000 | 8.0 | 48.0 | 0.0 | 1.0 | 7.0 | 8.0 | 12.0 | 4.5 | 1.5 | 9.0 | 0.5 | 0.5 |
20 | Bulgaria | 7 364 570 | 17.0 | 10.5 | 0.0 | 3.0 | 11.0 | 5.0 | 4.5 | 1.5 | 19.5 | 24.0 | 2.0 | 0.5 |
21 | Serbia | 7 120 666 | 15.0 | 7.0 | 0.5 | 0.5 | 6.5 | 1.5 | 6.5 | 0.5 | 36.0 | 20.5 | 3.0 | 1.0 |
22 | Denmark | 5 580 413 | 12.0 | 44.0 | 0.5 | 0.0 | 2.5 | 1.0 | 31.0 | 5.0 | 0.5 | 2.5 | 0.0 | 1.0 |
23 | Finland | 5 421 827 | 7.5 | 3.5 | 58.5 | 0.0 | 0.0 | 0.0 | 28.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.5 |
24 | Slovakia | 5 397 036 | 42.0 | 23.0 | 2.0 | 0.0 | 4.0 | 1.0 | 6.0 | 1.0 | 10.0 | 9.0 | 1.0 | 1.5 |
25 | Norway | 5 033 675 | 27.0 | 28.0 | 4.0 | 0.0 | 1.0 | 0.5 | 34.0 | 1.0 | 0.0 | 1.0 | 0.5 | 3.0 |
26 | Bosnia and Herzegovina | 4 622 163 | 13.5 | 4.0 | 0.0 | 1.0 | 6.0 | 2.0 | 2.5 | 0.5 | 50.0 | 14.5 | 2.5 | 0.0 |
27 | Ireland | 4 588 252 | 2.50 | 81.0 | 0.0 | 0.0 | 1.0 | 1.0 | 6.0 | 5.0 | 1.0 | 2.0 | 0.0 | 0.0 |
28 | Croatia | 4 483 804 | 24.0 | 8.5 | 0.5 | 1.0 | 6.0 | 2.5 | 5.5 | 1.0 | 37.0 | 10.0 | 1.0 | 0.5 |
29 | Moldova | 3 559 500 | 20.0 | 14.0 | 3.0 | 1.0 | 10.0 | 6.0 | 3.0 | 2.0 | 30.0 | 9.0 | 1.0 | 1.0 |
30 | Albania | 3 002 859 | 9.0 | 16.0 | 0.0 | 2.0 | 19.5 | 1.5 | 2.0 | 1.5 | 12.0 | 27.5 | 1.0 | 0.0 |
31 | Lithuania | 2 988 400 | 38.0 | 5.0 | 45.0 | 0.0 | 0.0 | 0.0 | 6.0 | 1.0 | 3.0 | 1.0 | 0.5 | 0.5 |
32 | Latvia | 2 217 053 | 40.0 | 10.0 | 40.0 | 0.0 | 0.5 | 0.0 | 6.0 | 1.0 | 1.0 | 0.5 | 0.5 | 0.5 |
33 | Macedonia | 2 058 539 | 14.5 | 10.5 | 0.5 | 2.0 | 12.5 | 4.0 | 3.0 | 1.0 | 27.0 | 20.5 | 2.0 | 0.5 |
34 | Slovenia | 2 055 496 | 34.5 | 23.5 | 0.0 | 1.0 | 3.0 | 1.5 | 9.5 | 2.0 | 22.0 | 3.0 | 0.0 | 0.0 |
35 | Estonia | 1 294 236 | 32.0 | 8.0 | 34.0 | 0.0 | 1.0 | 0.0 | 15.0 | 0.5 | 3.0 | 2.5 | 3.5 | 0.5 |
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Ragulskaya, M.V. Solar Cycles and Covid-19 Pandemic Paradoxes. Geomagn. Aeron. 63, 984–995 (2023). https://doi.org/10.1134/S0016793223070198
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DOI: https://doi.org/10.1134/S0016793223070198