1. Phylogenetic Analysis in the
Genetic Epidemiology of SARS-CoV-
2: Insights from Multiple Studies
• SARS-CoV-2 a novel coronavirus was first identified in
December 2019 in Wuhan, Hubei Province, China.
• Genetic Epidemiology is the study of contribution of
genetic factor in health or disease in family and
population and how genes interplay with
• Phylogenetic analysis is a key tool in genetic
epidemiology that allows researchers to reconstruct
the evolutionary relationships among different SARS-
CoV-2 strains and track the spread of the virus
3. Problem Statement
• SARS-CoV-2 has spread globally, leading to a
• Which resulted in millions of infections and
deaths worldwide, significantly impacting
healthcare systems, economies, and daily life.
• it's crucial to understand its transmission
dynamics and genetic diversity in controlling
its spread and developing effective
• To examine the genetic diversity, evolutionary
relationship, and transmission of virus.
• This study may aid in controlling viral spread.
It emphasizes how important phylogenetics is
for understanding the genetic epidemiology of
SARS-CoV-2 and how it could influence clinical
and public health decisions.
• In conclusion, the studies highlight the important
role that phylogenetic analysis plays in the
genetic epidemiology of SARS-CoV-2.
• Phylogenetic analysis can provide valuable
insights into the transmission dynamics and
spread of SARS-CoV-2, including the identification
of local transmission clusters and the tracking of
viral evolution over time and complementing
traditional epidemiological methods
COVID-19 is characterized by fever, cough, sore throat, fatigue, body aches, loss of taste or smell, and shortness of breath. However, some individuals may remain asymptomatic or have only mild symptoms, while others may develop severe respiratory distress, pneumonia, or other complications.
From Alpha to Delta—Genetic Epidemiology of SARS-CoV-2 (hCoV-19) in Southern Poland
The maximum likelihood phylogeny of Southern Poland whole-genome sequences generated in Nextclade. The amino acid substitutions were used and the maximum likelihood phylogenetic tree was developed for each wave. The different shades of blue, green, gray, and orange dots in the phylogenetic tree show the distribution of SARS-CoV-2 samples in the respective clades. The lineages that share the same mutations group together. The longer lines mean more mutations and sequences on single long lines mean unique mutations. The B.1.617.2 clade carried the highest number of mutations, followed by B.1.1.7, while clade P.1 and B.1.621.1 showed different mutations. The B.1.621.1 clade, despite other clades’ spike protein mutations, also had the extra substitution Y145H, while P.1 had additional sequence changes resulting in R190S, T638I, T1027I, and V1176F. Legend: 20A (Pango: B.1.160), 20B (Pango: B.1.1.277), 20C (Pango: B.1.367), 20D (Pango: C.36), 20J (Pango: P.1.1), 20I (Pango: B.1.1.7), 21H (Pango: B.1.621), and 21A (Pango: B.1.617.2).
Genetic epidemiology using whole genome sequencing and haplotype networks revealed the linkage of SARSCoV-2 infection in nosocomial outbreak
Figure 2. Phylogenetic tree analysis of SARS-CoV-2 genome from SUH. A phylogenetic tree was created using the genomes of the 32 isolates from SUH with the NJ method, as described in the Methods section
High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing
Phylogenetic trees generated by Nextstrain. 469 COVIDseq genomes reported from this study are highlighted. The 469 genomes cluster under clade A2a, I/A3i and B4, with A2a being the dominant clade.