Comparing Two Sample Pooling Strategies For Sars-Cov-2 Rna Detection For Efficient Screening Of Covid-19

JOURNAL OF MEDICAL VIROLOGY(2021)

Cited 20|Views19
No score
Abstract
The emerging pandemic of coronavirus disease 2019 (COVID-19) has affected over 200 countries and resulted in a shortage of diagnostic resources globally. Rapid diagnosis of COVID-19 is vital to control the spreading of the disease, which, however, is challenged by limited detection capacity and low detection efficiency in many parts of the world. The pooling test may offer an economical and effective approach to increase the virus testing capacity of medical laboratories without requiring more laboratory resources such as laboratory workers, testing reagents, and equipment. In this study, the sample pools of 6 and 10 were detected by a real-time reverse transcription-polymerase chain reaction assay targeting ORF1ab and N genes of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Each pool consisted of five or nine negative SARS-CoV-2 samples and one positive counterpart with varying viral loads. Two different strategies of sample pooling were investigated and the results were compared comprehensively. One approach was to pool the viral transport medium of the samples in the laboratory, and the other was to pool swab samples during the collection process. For swab pooling strategy, qualitative results of SARS-CoV-2 RNA, specific tests of ORF1ab and N genes, remained stable over the different pool sizes. Together, this study demonstrates that the swab pooling strategy may serve as an effective and economical approach for screening SARS-CoV-2 infections in large populations, especially in countries and regions where medical resources are limited during the pandemic and may thus be potential for clinical laboratory applications.
More
Translated text
Key words
COVID-19, RT-PCR test, sample pooling strategy, SARS-CoV-2
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined