Epidemiological Features and Phylogeny of SARS-CoV-2 Circulating in the Southeast Asia in Early Pandemic

Abstract

Objectives: This study aims to understand the epidemiological and level of genetic similarity in the SARS-CoV-2 from different geographical areas in The Southeast Asia Region during an early pandemic. Methods: The data on COVID-19 cases in Southeast Asia was collected from https://worldometer.info/ and extracted independently. Complete genome SARS-CoV-2 nucleotide sequence data was obtained from GISAID and NCBI online platforms. The sequences were aligned using MEGA X software and identified RdRp and Spike genes using UGENE software. The phylogenetic was constructed using MEGA X software to know the similarity of these genes among isolates in the Southeast Asia region. Results: The result showed that the first case in Southeast Asia was reported in January 2020. The highest number of COVID-19 cases and death were reported from populous and suffering countries. The phylogenetic results showed an identical solid (100%) among isolates, except for the Philippines-5 isolate. The Wuhan-Hu-1 (China) SARS-CoV-2 isolate (Acc. NC_045512) was transmitted to other countries in Southeast Asia regions with various mutations in the spike protein. Conclusion: During the early pandemic, all countries in the Southeast Asia regions reported COVID-19 cases. Indonesia became the country with the highest number of COVID-19 cases and deaths. The level of similarity of the RdRp gene in the SARS-CoV-2 in Southeast Asia is higher than the Spike genes. J Microbiol Infect Dis 2022; 12(4):139-148.

Keywords

• Epidemiology
• Phylogeny
• SARS-Cov-2
• Pandemic

References

1. 1. Lu R, Zhao X, Li J, et al. 2020. Genomic characterization and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet 2020; 395: 565–574.
2. 2. Khailany RA, Safdar M, Ozaslan M. Genomic characterization of a novel SARS-CoV-2. Gene Rep 2020; 19: 100682.
3. 3. Zhou L, Ayeh SK, Chidambaram V, et al. Modes of transmission of SARS-CoV-2 and evidence for preventive behavioral interventions. BMC Infect Dis 2021; 21: 496.
4. 4. Ozaslan M, Safdar M, Halil KI, Khailany RA. Practical measures to prevent COVID-19: a mini-review. J Biol Sci 2020; 20: 100–102.
5. 5. COVID Live. Accessed by https://www.worldometers.info/coronavirus/.
6. 6. Tordoff DM, Greninger AL, Roychoudhury P, et al. Phylogenetic estimates of SARS-CoV-2 introductions into Washington State. Lancet Reg Health Am 2021;1:100018.
7. 7. Pachetti M, Marini B, Benedetti F, et al. Emerging SARS-CoV-2 mutation hot spots include a novel RNA-dependent-RNA polymerase variant. J Transl Med 2020; 18(1):179.
8. 8. Global Initiative on Sharing ALL Influenza Data (GISAID). Accessed by https://www.gisaid.org/.

9. 9. Yao H, Lu X, Chen Q, et al. Patient-derived SARS-CoV-2 mutations impact viral replication dynamics and infectivity in vitro and with clinical implications in vivo. Cell Discov 2020; 6: 76.
10. 10. Hakim MS, Annisa L, Supriyati E, et al. Current understanding of the origin, molecular biology, and continuing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). J Med Sci 2020; 52(3): 54-66.
11. 11. The National Center of Biotechnology Information (NCBI). Accessed by https://ncbi.nlm.nih.gov/.
12. 12. Zhu N, Zhang D, Wang W, et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med 2020; 382:8.
13. 13. Abdullahi IN, Emeribe AU, Ajayi OA, Oderinde BS, Amadu DO, Osuji AI. Implications of SARS-CoV-2 genetic diversity and mutations on pathogenicity of the COVID-19 and biomedical interventions. J Taibah Univ Med Sci 2020; 15(4): 258-264.
14. 14. Dowd JB, Andriano L, Brazel DM, Mills MC. Demoghrapich science aids in understanding the spread and fatality rates of Covid19. PNAS 2020; 117: 9696-9698.
15. 15. Aisyah DN, Mayadewi CA, Diva H, Kozlakidis Z, Siswanto, Adisasmito W. A spatial-temporal description of the SARS-CoV-2 infections in Indonesia during the first six months of the outbreak. PLoS ONE 2020; 15(12): e0243703.
16. 16. Mboi N, Surbakti IM, Trihandini I, et al. On the road to universal health care in Indonesia, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet 2018; 392: 581–591. 17. World Health Organization (WHO). 2018. Noncommunicable diseases country profiles. License: CC BY-NC-SA 3.0 IGO. ISBN 978-92-4-151462-0.
17. 18. Clark A, Jit M, Gash CW, et al. Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modeling study. Lancet Glob Health 2020; 8: e1003–17.
18. 19. Duffy S. Why are RNA virus mutation rates so damn high? PLoS Biol 2018; 16(8): e3000003.
19. 20. Tabibzadeh A, Zamani F, Laali A, et al. SARS-CoV-2 Molecular and Phylogenetic analysis in COVID-19 patients: A preliminary report from Iran. Infection, Genetics, and Evolution; 2020 ;84: 104387.
20. 21. Walls AC, Park Y-J, Tortorici MA, Wall A, McGuire AT, Veesler D. Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein. Cell 2020; 180: 281–292.
21. 22. Chan JF, Kong K, Zhu Z, et al. Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan. Emerg. Microbes Infect 2020; 9.
22. 23. Becerra-Flores M, Cardozo T. SARS-CoV-2 viral spike G614 mutation exhibits a higher case fatality rate. Int J Clin Pract 2020; 74(8): e13525.
23. 24. Zhang H, Penninger JM, Li Y, Zhong N, Slutsky AS. Angiotensin-converting enzyme 2 (ACE2) as a SARS-CoV-2 receptor: molecular mechanisms and potential therapeutic target. Intensive Care Med 2020; 46(4): 586-590.