Genetic epidemiology using whole genome sequencing and haplotype networks revealed the linkage of SARS-CoV-2 infection in nosocomial outbreak.

Fumihiro Ishikawa, Yuko Udaka, Hideto Oyamada, Keiko Ishino, Issei Tokimatsu, Hironori Sagara, Yuji Kiuchi
Author Information
  1. Fumihiro Ishikawa: PCR Centre for COVID-19, Showa University Hospital, Tokyo, Japan.
  2. Yuko Udaka: PCR Centre for COVID-19, Showa University Hospital, Tokyo, Japan.
  3. Hideto Oyamada: PCR Centre for COVID-19, Showa University Hospital, Tokyo, Japan.
  4. Keiko Ishino: PCR Centre for COVID-19, Showa University Hospital, Tokyo, Japan.
  5. Issei Tokimatsu: Division of Infectious Diseases, Department of Internal Medicine, Showa University School of Medicine, Tokyo, Japan.
  6. Hironori Sagara: Division of Respiratory Medicine and Allergology, Department of Internal Medicine, Showa University School of Medicine, Tokyo, Japan.
  7. Yuji Kiuchi: PCR Centre for COVID-19, Showa University Hospital, Tokyo, Japan.

Abstract

BACKGROUND: A characteristic feature of SARS-CoV-2 is its ability to transmit from pre- or asymptomatic patients, complicating the tracing of infection pathways and causing outbreaks. Despite several reports that whole genome sequencing (WGS) and haplotype networks are useful for epidemiologic analysis, little is known about their use in nosocomial infections.
AIM: We aimed to demonstrate the advantages of genetic epidemiology in identifying the link in nosocomial infection by comparing single nucleotide variations (SNVs) of isolates from patients associated with an outbreak in Showa University Hospital.
METHODS: We used specimens from 32 patients in whom COVID-19 had been diagnosed using clinical reverse transcription-polymerase chain reaction tests. RNA of SARS-CoV-2 from specimens was reverse-transcribed and analysed using WGS. SNVs were extracted and used for lineage determination, phylogenetic tree analysis, and median-joining analysis.
FINDINGS: The lineage of SARS-CoV-2 that was associated with outbreak in Showa University Hospital was B.1.1.214, which was consistent with that found in the Kanto metropolitan area during the same period. Consistent with canonical epidemiological observations, haplotype network analysis was successful for the classification of patients. Additionally, phylogenetic tree analysis revealed three independent introductions of the virus into the hospital during the outbreak. Further, median-joining analysis indicated that four patients were directly infected by any of the others in the same cluster.
CONCLUSION: Genetic epidemiology with WGS and haplotype networks is useful for tracing transmission and optimizing prevention strategies in nosocomial outbreaks.

Keywords

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Word Cloud

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