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Research Article Open access CC BY 4.0

Phylogenetic Analysis to Detect COVID Superspreaders

John R. Jungck, Hajae Ko

Microbiology Research Journal International · pp. 36–43 · Published 12 Oct 2023

10.9734/mrji/2023/v33i81400

Abstract

Aims: Detection of superspreading events by phylogenetic analysis of nucleotide sequences from a population of individuals collected from a narrow time interval. Study Design: Retrieve nucleic acid sequences, construct multiple sequence alignments, and build phylogenetic networks to determine sources of infection. Place and Duration of Study: This study was performed at the Delaware Biotechnology Institute of the University of Delaware over the period: June-August, 2022. The data used were from the GIS AID database. Methodology: Sequences for analysis were sampled from the GISAID initiative’s open-access SARS-CoV-2 genome database. We selected high-quality nucleotide sequences submitted by Delaware labs between March 18 and April 14, 2021, an important period of 4 weeks which saw the Alpha variant spread rapidly in the Delaware population. Results: Four sources accounted for 215 of the 401 sequences. In other words, 54% of all cases were rooted in just five sources. Conclusion: Thus, superspreading seems to have a major impact on the proportion of individuals in a population affected with COVID.

COVID superspreaders phylogenetic networks

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