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Chronicling the 3-year evolution of the COVID-19 pandemic: analysis of disease management, characteristics of major variants, and impacts on pathogenicity

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Abstract

Announced on December 31, 2019, the novel coronavirus arising in Wuhan City, Hubei Province resulted in millions of cases and lives lost. Following intense tracking, coronavirus disease 2019 (COVID-19) was declared a pandemic by the World Health Organization (WHO) in 2020. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified as the cause of COVID-19 and the continuous evolution of the virus has given rise to several variants. In this review, a comprehensive analysis of the response to the pandemic over the first three-year period is provided, focusing on disease management, development of vaccines and therapeutics, and identification of variants. The transmissibility and pathogenicity of SARS-CoV-2 variants including Alpha, Beta, Gamma, Delta, and Omicron are compared. The binding characteristics of the SARS-CoV-2 spike protein to the angiotensin-converting enzyme 2 (ACE2) receptor and reproduction numbers are evaluated. The effects of major variants on disease severity, hospitalisation, and case-fatality rates are outlined. In addition to the spike protein, open reading frames mutations are investigated. We also compare the pathogenicity of SARS-CoV-2 with SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). Overall, this study highlights the strengths and weaknesses of the global response to the pandemic, as well as the importance of prevention and preparedness. Monitoring the evolution of SARS-CoV-2 is critical in identifying and potentially predicting the health outcomes of concerning variants as they emerge. The ultimate goal would be a position in which existing vaccines and therapeutics could be adapted to suit new variants in as close to real-time as possible.

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Acknowledgements

EP and RCB are supported by an Australian Government Research Training Program Scholarship. We thank the National Computing Infrastructure (NCI), and the Pawsey Supercomputing Centre in Australia (funded by the Australian Government). Further, we thank the Spartan High Performance Computing service (University of Melbourne), and the Partnership for Advanced Computing in Europe (PRACE) for awarding the access to Piz Daint, hosted at the Swiss National Supercomputing Centre (CSCS), Switzerland.

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  1. Eleni Pitsillou and Yiping Yu contributed equally to this work.

Authors and Affiliations

  1. Epigenomic Medicine Laboratory at prospED, Carlton, VIC, 3053, Australia

    Eleni Pitsillou, Raymond C. Beh, Julia J. Liang & Tom C. Karagiannis

  2. School of Science, STEM College, RMIT University, Melbourne, VIC, 3001, Australia

    Eleni Pitsillou, Raymond C. Beh, Julia J. Liang & Andrew Hung

  3. Department of Microbiology and Immunology, The University of Melbourne, Parkville, VIC, 3010, Australia

    Yiping Yu & Tom C. Karagiannis

  4. Department of Clinical Pathology, The University of Melbourne, Parkville, VIC, 3010, Australia

    Tom C. Karagiannis

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  1. Eleni Pitsillou
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  2. Yiping Yu
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  3. Raymond C. Beh
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Contributions

TCK and AH conceptualized the aims and methodology, were involved in supervision, and production of the first draft of the manuscript. EP and YY curated data. RCB created the online interactive timeline. EP, YY, RCB, and JJL performed data analysis and produced the first draft of the manuscript. All authors contributed to editing and reviewing the manuscript.

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Correspondence to Tom C. Karagiannis.

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Pitsillou, E., Yu, Y., Beh, R.C. et al. Chronicling the 3-year evolution of the COVID-19 pandemic: analysis of disease management, characteristics of major variants, and impacts on pathogenicity. Clin Exp Med 23, 3277–3298 (2023). https://doi.org/10.1007/s10238-023-01168-0

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