2. Introduction
• 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 environmental factors
• 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 pandemic
• 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 interventions.
4. Objectives
• 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.
9. Conclusions
• 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
Notes de l'éditeur
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.