摘要
To the Editor:As of August 9,2020,the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)has infected 19,432,244 people and caused 721,594 deaths globally.To timely identify the infected persons,nucleic acid detection screenings have been carried out for high-infection risk groups in areas known to have coronavirus disease 19(COVID-19)cases,such as Wuhan,Beijing,and Xinjiang.The rapid identification of infected patients and the implementation of quarantine measures play an important role in preventing the transmission of SARS-CoV-2.However,there are some issues associated with large-scale screening for this virus.The consumption of equipment and reagents for specimen collection and detection is high,resulting in elevated screening costs.Moreover,with the increase in the number of samples collected,the testing capabilities of medical institutions have reached a saturation point,hindering the speed and scope of large-scale screenings.For this reason,the mixed detection after RNA extraction(detection in a mixture of nucleic acids extracted from several patients)or before RNA extraction(detection in a mixture of pharyngeal swab transfer buffer obtained from different patients before nucleic acid extraction)has been proposed in many regions.[1]However,both the pooling of swab transfer buffer before nucleic acid extraction and pooling of RNA after nucleic acid extraction inevitably cause dilution of samples and decrease of detection sensitivity.However,there is still a lack of research on how to effectively improve the screening efficiency and control the decrease of sensitivity caused by dilution in an appropriate range.In this study,we designed a novel 10-in-1 test(ten pharyngeal swab samples from ten individuals were placed in one custom-made virus collection tube[CMT]for nucleic acid extraction and testing)by optimizing the current mixed acquisition technique,and after a promising pilot test.
基金
This work was supported by the Emergency Scientific Research Project for Prevention and Control of COVID-19 of Liaoning Province(the fourth batch,No.2020JH2/10300175)。