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020 _aTHE0010291 (Local)
_qHardback
040 _aUMPSA
_beng
_cUMPSA
_erda
090 _aFIST .S536 2025 r Bc.
100 0 _aChew, Sian Hui,
_eauthor.
245 1 0 _aGenomic epidemiology of Sars-Cov-2 in Malaysia /
_cChew Sian Hui
264 1 _aKuantan, Pahang :
_bUMPSA,
_c2025
264 4 _c© 2025
300 _axiii, 108 pages :
_billustrations ;
336 _2rdacontent
_atext
337 _2rdamedia
_aunmediated
338 _2rdacarrier
_avolume
347 _2rda
_atext file
_bPDF
500 _aFaculty of Industrial Sciences and Technology
502 _aFinal Year Report (Bachelor of Applied Science in Industrial Biotechnology) -- Universiti Malaysia Pahang Al-Sultan Abdullah - 2025
504 _aInclude bibliographical reference
520 3 _aThe COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has posed unprecedented challenges to global health systems. This research project aims to elucidate the genomic epidemiology of SARS-CoV-2 in Malaysia by analysing whole genome sequences of SARS-CoV-2 sourced from the GISAID EpiCoV databases. Bioinformatics tools were used to construct phylogenetic tree and investigate the evolutionary relationships among the virus strains circulating in Malaysia from the beginning of the pandemic until 30 November 2024. The research began with the collection of genomic epidemiological data of SARS-CoV-2 from KKMNOW and Ministry of Health Malaysia (MOH) websites, including daily confirmed cases, death cases, hospitalizations, and daily testing performed. The genomic epidemiological data collected was compiled in Excel files and visualised into choropleth maps using Tableau Public to depict the spatial distribution of key indicators across different states in Malaysia. The dataset of VOIs and VOCs collected from the GISAID EpiCoV databases were visualised into choropleth map to track the circulation of variants within Malaysia. The analysis of SARS-CoV-2 sequences was conducted by retrieving the data from GISAID EpiCoV databases. The phylogenetic tree was constructed using Nextstrain – Nextclade tool and visualised using Auspice.us to understand the evolution of SARSCoV-2 variants. The findings suggested that nine distinct waves of COVID-19 were identified, with the initial case reported on 25 January 2020. Despite record-high cases during the fifth wave, health conditions stabilized, leading to varying trends in subsequent waves. A decline in COVID-19 outbreaks was observed starting from the sixth wave of the pandemic. In 2024, Malaysia transitioned into an endemic phase due to the relatively low of reported confirmed cases. Selangor consistently reported high numbers of cases, deaths, hospitalizations, and diagnostic tests, linked to the population density. The genomic surveillance revealed that AY.59 as the predominant variant circulating in Malaysia, followed by AY.79. AY.23 was dominated in Sarawak, accounting for 61.34% (2063 high coverage sequences submitted). AY.76 was predominated in Sabah and Labuan, accounting for 38.38% (137 sequences) and 40% (16 sequences), respectively. BA.2 emerged as the most prevalent variant in Selangor, accounting for 40.24% (957 sequences). The top 5 SARS-CoV-2 lineages emerged during 2024 were JN.1, KP.2.3, XDY, KP.1.1.3, and KP.3. The phylogenetic analysis showed the ubiquity of Omicron variants with diverse sub-lineages such as ‘21L’ and ‘23I’, along with novel recombinant lineages like XBB and variant JN.1. This study provided the comprehension knowledge of the genomic epidemiology of SARS-CoV-2 in Malaysia with valuable insights into the evolution and transmission patterns of the virus. Genetic data and geographical dispersion maps are essential assets for policymakers and health professionals in effectively managing ongoing pandemic challenges.
610 2 0 _aFaculty of Industrial Sciences and Technology
_xDissertations
650 0 _aUniversities and colleges
_xDissertations
650 0 _aFinal Year Report
_xDissertations
856 _uhttp://umpir.ump.edu.my/id/eprint/45600
942 _2lcc
_cPSM
999 _c103898
_d103904