Molecular epidemiological analysis of COVID-19 imported cases in Ruili from July to November, 2021
Chinese Journal of Disease Control and Prevention
; 27(2):157-163, 2023.
Article
in Chinese
| Scopus | ID: covidwho-2306557
ABSTRACT
Objective To analyze the epidemiological and genomic characteristics of COVID-19 cases imported by land in Ruili, and to provide reference for border epidemic prevention and control in Yunnan Province. Methods We collected information about SARS-CoV-2 infected individuals from overseas land in Ruili, Yunnan from July to November, 2021. The epidemiological characteristics were statistically analyzed. The second-generation sequencing platform of Illumina was used to conduct high-through-put sequencing on the selected 40 positive samples and to analyze their genotyping and variation characteristics. Results During the study period,Ruili City reported 796 COVID-19 cases from abroad.The median age of COVID-19 cases was 28.5 years (Interquantile range 10, range 1–85). The gender ratio between men and women was 4.61 1, Most of these infected individuals engaged in business services, accounting for 49.75% (396/796) , 95.60% of COVID-19 cases were mild and moderate cases. The sequencing results of 34 cases can be divided into three clades according to Nextstrain typing method, including 24 cases belong to 21A(Delta) clade, 9 cases belong to 21I(Delta) clade and 1 case belongs to 20I (Alpha V1) clade. Conclusions The virus genotypes of the cases in this study were mainly divided into three branches and there were some differences among them, most of which were Delta mutants.We should continue to implement border control measures and continue to monitor the virus mutation of imported cases, so as to evaluate the threat of the mutant strain to the current situation of epidemic prevention and control in Yunnan Province. © 2023, Publication Centre of Anhui Medical University. All rights reserved.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Observational study
Language:
Chinese
Journal:
Chinese Journal of Disease Control and Prevention
Year:
2023
Document Type:
Article
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