The Dominance of Severe Acute Respiratory Syndrome Coronavirus 2 B.1.617 and Its Sublineages and Associations with Mortality during the COVID-19 Pandemic in India between 2020 and 2021

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  • 1 Department of Economics, SDM Institute for Management Development, Mysuru, Karnataka, India;
  • | 2 Department of Quantitative Methods, SDM Institute for Management Development, Mysuru, Karnataka, India;
  • | 3 Nitte (Deemed to Be University), Division of Infectious Diseases, Nitte University Centre for Science Education and Research, Deralakatte, Mangalore, Karnataka, India

As the COVD-19 pandemic spreads, several new severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) variants with various mutations across the genome have arisen, and they appear to be the greater risk to global public health. In this study, we have performed molecular characterization of SARS-COV-2 circulating in India between January 2020 and May 2021. Phylogenetic analysis of the SARS-COV-2 reported in the first and second waves of the outbreak showed the evolutionary hierarchy of SARS-COV-2 that was dispersed across the evolutionary tree of SARS-COV-2 with six major next strain clades: 19A (5.3%), 20A (29.9%), 20B (24.9%), 20I-Alpha, V1 (7.4%), 21A-Delta (17.2%), and 21B-Kappa (12.7%). Among the observed clades, 21A-Delta and 21B-Kappa belonging to the B.1.617 and its sublineages are the two notable clades that dominated approximately 78% of the total SARS-COV-2 genomes reported during April and May 2021. This study has also established a link between different SARS-COV-2 variants and risk of mortality during the COVID-19 epidemic using multivariable logistic regression model for patient-level data. The estimated model demonstrates that the risk of mortality of the COVID 19 patients infected by variant B.1.617 and/or its sublineages is much higher than the other preexisting SARS-COV-2 variants, especially among individuals over 45 years of age, regardless of gender. Considering the transmissibility of the B.1.617 and its sublineages and its potential impact to the public health, real-time analysis of COVID-19 cases coupled with stringent genomics surveillance are promising tools to develop and adapt stringent measures to contain and reduce the impact of SARS-COV-2.

Author Notes

Address correspondence to Bakilapadvu Venkatraja, SDM Institute for Management Development, Mysuru 570011, India, E-mail: venkatraja@sdmimd.ac.inor Ballamoole Krishna Kumar, Division of Infectious Diseases, Nitte University Centre for Science Education and Research, Nitte (Deemed to be University), Mangalore 575018, India, E-mail: krishnakumarb@nitte.edu.in.

Authors’ addresses:Bakilapadvu Venkatraja, Department of Economics, SDM Institute for Management Development, Mysuru, India, E-mail: venkatraja@sdmimd.ac.in. Gali Srilakshminarayana, Department of Quantitative Methods, SDM Institute for Management Development, Mysuru, Karnataka, India, E-mail: lakshminarayana@sdmimd.ac.in. Ballamoole Krishna Kumar, Division of Infectious Diseases, Nitte University Centre for Science Education and Research, Nitte (Deemed to be University), Mangalore, India, E-mail: krishnakumarb@nitte.edu.in.

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