Large-scale synchronized replacement of Alpha (B.1.1.7) variant by the Delta (B.1.617.2) variant of SARS-COV-2 in the COVID-19 pandemic

Yuan Liu; Anyin Feng; Shi Zhao; Weiming Wang; Daihai He; Yuan Liu; Anyin Feng; Shi Zhao; Weiming Wang; Daihai He

doi:10.3934/mbe.2022165

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 4: 3591-3596. doi: 10.3934/mbe.2022165

Previous Article Next Article

Brief report

Large-scale synchronized replacement of Alpha (B.1.1.7) variant by the Delta (B.1.617.2) variant of SARS-COV-2 in the COVID-19 pandemic

1.
Department of Applied Mathematics, The Hong Kong Polytechnic University, HKSAR, China
2.
JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China
3.
CUHK Shenzhen Research Institute, Shenzhen, China
4.
School of Mathematics and Statistics, Huaiyin Normal University, Huaian, 223300, China

Received: 30 November 2021 Revised: 17 January 2022 Accepted: 18 January 2022 Published: 07 February 2022

In this work, we report a large-scale synchronized replacement pattern of the Alpha (B.1.1.7) variant by the Delta (B.1.617.2) variant of SARS-COV-2. We argue that this phenomenon is associated with the invasion timing and the transmissibility advantage of the Delta (B.1.617.2) variant. Alpha (B.1.1.7) variant skipped some countries/regions, e.g. India and neighboring countries/regions, which could have led to a mild first wave before the invasion of the Delta (B.1.617.2) variant, in term of reported COVID-deaths per capita.
- variants of concern,
- Delta (B.1.617.2) variant,
- Alpha (B.1.1.7) variant,
- synchronization,
- SARS-COV-2
Citation: Yuan Liu, Anyin Feng, Shi Zhao, Weiming Wang, Daihai He. Large-scale synchronized replacement of Alpha (B.1.1.7) variant by the Delta (B.1.617.2) variant of SARS-COV-2 in the COVID-19 pandemic[J]. Mathematical Biosciences and Engineering, 2022, 19(4): 3591-3596. doi: 10.3934/mbe.2022165

Related Papers:

Abstract

In this work, we report a large-scale synchronized replacement pattern of the Alpha (B.1.1.7) variant by the Delta (B.1.617.2) variant of SARS-COV-2. We argue that this phenomenon is associated with the invasion timing and the transmissibility advantage of the Delta (B.1.617.2) variant. Alpha (B.1.1.7) variant skipped some countries/regions, e.g. India and neighboring countries/regions, which could have led to a mild first wave before the invasion of the Delta (B.1.617.2) variant, in term of reported COVID-deaths per capita.

References

[1]	C. Wang, Z. Wang, G. Wang, J. Y. N. Lau, K. Zhang, W. Li, COVID-19 in early 2021: Current status and looking forward, Sig. Transduct Targeted Ther., 6 (2021), 1–14. http://doi.org/10.038/s41392-021-00527-1 doi: 10.038/s41392-021-00527-1
[2]	T. Chookajorn, T. Kochakarn, C. Wilasang, N. Kotanan, C. Modchang, Southeast Asia is an emerging hotspot for COVID-19, Nat Med., 27 (2021), 1495–1496. https://doi.org/10.1038/s41591-021-01471-x doi: 10.1038/s41591-021-01471-x
[3]	M. Vassallo, S. Manni, C. Klotz C, et al., Patients admitted for variant alpha COVID-19 have poorer outcomes than those infected with the old strain, J. Clin. Med., 10 (2021), 3550. https://doi.org/10.3390/jcm10163550 doi: 10.3390/jcm10163550
[4]	T. Farinholt, H. Doddapaneni, X. Qin, et al., Transmission event of SARS-CoV-2 Delta variant reveals multiple vaccine breakthrough infections, BMC Med., 19 (2021), 1–6. https://doi.org/10.1186/s12916-021-02103-4 doi: 10.1186/s12916-021-02103-4
[5]	Y. Liu, A. A. Gayle, A. Wilder-Smith, J. Rocklöv, The reproductive number of COVID-19 is higher compared to SARS coronavirus, J. Travel Med., 27 (2020), taaa021. https://doi.org/10.1093/jtm/taaa021 doi: 10.1093/jtm/taaa021
[6]	Y. Liu, J. Liu, K. S. Plante, J. A. Plante, X. P. Xie, X. W. Zhang, et al., The N501Y spike substitution enhances SARS-CoV-2 infection and transmission, Nature, (2021), 1–9. https://doi.org/10.1038/s41586-021-04245-0 doi: 10.1038/s41586-021-04245-0
[7]	O. Mor, M. Mandelboim, S. Fleishon, E. Bucris, D. Bar-Ilan, M. Linial, et al., The rise and fall of a local SARS-CoV-2 variant with the spike protein mutation L452R, Vaccines, 9 (2021), 937. https://doi.org/10.3390/vaccines9080937 doi: 10.3390/vaccines9080937
[8]	S. Shiehzadegan, N. Alaghemand, M. Fox, V. Venketaraman, Analysis of the delta variant B. 1.617. 2 COVID-19, Clin. Pract., 11 (2021), 778–784. https://doi.org/10.3390/clinpract11040093 doi: 10.3390/clinpract11040093
[9]	N. Ghosh, I. Saha, J. P. Sarkar, U. Maulik, Strategies for COVID-19 epidemiological surveillance in India: overall policies till June 2021, Frontiers Public Health, 9 (2021). https://doi.org/10.3389/fpubh.2021.708224 doi: 10.3389/fpubh.2021.708224
[10]	S. Shrivastava, S. T. Mhaske, M. S. Modak, R. G. Virkar, S. S. Pisal, A. C. Mishra, et al., Emergence of two distinct variants of SARS-CoV-2 and explosive second wave of COVID-19: An experience from a tertiary care hospital, Pune, India, Arch. Virol., (2022), 1–11. https://doi.org/10.1007/s00705-021-05320-7 doi: 10.1007/s00705-021-05320-7
[11]	S. Khare, C. Gurry, L. Freitas, M. B. Schultz, G.Bach, A. Diallo, et al., GISAID's role in pandemic response, China CDC Weekly, 3 (2021), 1049. https://doi.org/10.46234/ccdcw2021.255 doi: 10.46234/ccdcw2021.255
[12]	S. Elbe, G. Buckland-Merrett, Data, disease and diplomacy: GISAID's innovative contribution to global health, Global challenges, 1 (2017), 33–46. https://doi.org/10.1002/gch2.1018 doi: 10.1002/gch2.1018
[13]	Y. Shu, J. McCauley, GISAID: Global intiative on sharing all influenza data—from vision to reality, Euro. surveill., 22 (2017). https://doi.org/10.2807/1560-7917.ES.2017.22.13.30494 doi: 10.2807/1560-7917.ES.2017.22.13.30494
[14]	S. Reardon, How the Delta variant achieves its ultrafast spread, Nature, 21 (2021). https://doi.org/10.1038/d41586-021-01986-w doi: 10.1038/d41586-021-01986-w
[15]	M. Cevik, N. D. Grubaugh, A. Iwasaki, P. Openshaw, COVID-19 vaccines: Keeping pace with SARS-CoV-2 variants, Cell, 184 (2021), 5077–5081. https://doi.org/10.1016/j.cell.2021.09.010 doi: 10.1016/j.cell.2021.09.010
[16]	P. Rohani, D. J. Earn, B. T. Grenfell, Opposite patterns of synchrony in sympatric disease metapopulations, Science, 286 (1999), 968–971. https://doi.org/10.1126/science.286.5441.968 doi: 10.1126/science.286.5441.968
[17]	P. Rohani, C. Green, N. Mantilla-Beniers, B. Grenfell, Ecological interference between fatal diseases, Nature, 422 (2003), 885–888. https://doi.org/10.1038/nature01542 doi: 10.1038/nature01542

Reader Comments

Your name:*

Email:*
© 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)